MANUAL FOR STATISTICS ON ENERGY CONSUMPTION IN HOUSEHOLDS - MESH PROJECT. Report 4: Compendium of best practices

Transcription

1 MANUAL FOR STATISTICS ON ENERGY CONSUMPTION IN HOUSEHOLDS - MESH PROJECT Report 4: Compendium of best practices 25 January 2013

2 INDEX 1. INTRODUCTION BEST PRACTICES BY STATISTICAL METHODS SURVEYS Survey Energy Consumption in Households (Cyprus) Residential Energy Consumption Survey (RECS) (USA) Survey Statistics on Energy Conpsumption in Households (Austria) Survey Energy Consumption in Households (Greece) Survey German Residential Energy Consumption Survey (Germany) Survey Energy Consumption in Households (Portugal) Survey Statistics on Energy Conpsumption in Households (Bulgaria) Similarities and differences found among the surveys ADMINISTRATIVE SOURCES EAP (energy advice procedure) data and EPC (energy performance certificate) data (Belgium) Energy Label of buildings database (Netherlands) Client files from energy companies (Netherlands) EPB (Flanders) (Belgium) Electricity, Natural Gas and LPG surveys (Spain) Similarities and differences found among the administrative sources IN SITU MEASUREMENTS SPAHOUSEC - SECH Project measures electricity consumption in 600 homes (Spain) Metering of domestic electricity use at apparatus level in 400 households (Sweden) Similarities and differences found between the in situ measurements MODELS Model of energy consumption in households (Slovenia) RAKLAMM calculation model for space and water heating (Finland) BREHOMES models national aggregates of domestic energy use (United Kingdom) Analysis of sectorial energy consumption by end-use (Switzerland) Matching the results of "Household electricity consumption survey" with "Household energy consumption survey" (Austria) Similarities and differences found among the models

3 2.5. INTEGRATED APPROACHES Spain Integrated Approach BEST PRACTICES BY GEOGRAPHICAL AREAS CYPRUS USA GREECE LATVIA SLOVENIA SPAIN AUSTRIA CONCLUSION INDEX OF TABLES TABLE 1. CYPRUS: CHARACTERISTICS ELEMENTS OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 2. CYPRUS: STRENGTHS AND WEAKNESSES OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 3. USA: CHARACTERISTIC ELEMENTS OF THE SURVEY RESIDENTIAL ENERGY CONSUMPTION SURVEY (RECS) TABLE 4. USA: STRENGTHS AND WEAKNESSES OF THE SURVEY RESIDENTIAL ENERGY CONSUMPTION SURVEY (RECS) TABLE 5. AUSTRIA: CHARACTERISTICS ELEMENTS OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 6. AUSTRIA: STRENGTHS AND WEAKNESSES OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 7. GREECE: CHARACTERISTICS ELEMENTS OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 8. GREECE: STRENGTHS AND WEAKNESSES OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 9. GERMANY: CHARACTERISTICS ELEMENTS OF SURVEY GERMAN RESIDENTIAL ENERGY CONSUMPTION... 24

4 TABLE 10. GERMANY: STRENGTHS AND WEAKNESSES OF SURVEY GERMAN RESIDENTIAL ENERGY CONSUMPTION TABLE 11. PORTUGAL: CHARACTERISTICS ELEMENTS OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 12. PORTUGAL: STRENGTHS AND WEAKNESSES OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 13. BULGARIA: CHARACTERISTICS ELEMENTS OF SURVEY STATISTICS ON ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 14. BULGARIA: STRENGTHS AND WEAKNESSES OF SURVEY STATISTICS ON ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 15. BELGIUM: CHARACTERISTICS ELEMENTS OF ADMINISTRATIVE SOURCE EAP DATA AND EPC DATA TABLE 16. BELGIUM: STRENGTHS AND WEAKNESSES OF ADMINISTRATIVE SOURCE EAP DATA AND EPC DATA TABLE 17. NETHERLANDS: CHARACTERISTICS ELEMENTS OF ADMINISTRATIVE SOURCE ENERGY LABEL OF BUILDINGS DATABASE TABLE 18. NETHERLANDS: STRENGTHS AND WEAKNESSES OF ADMINISTRATIVE SOURCE ENERGY LABEL OF BUILDINGS DATABASE TABLE 19. NETHERLANDS: CHARACTERISTICS ELEMENTS OF ADMINISTRATIVE SOURCE CLIENT FILES FROM ENERGY COMPANIES TABLE 20. NETHERLANDS: STRENGTHS AND WEAKNESSES OF ADMINISTRATIVE SOURCE CLIENT FILES FROM ENERGY COMPANIES TABLE 21. BELGIUM: CHARACTERISTIC ELEMENTS OF THE ADMINISTRATIVE SOURCE EPB (FLANDERS) TABLE 22. BELGIUM: STRENGTHS AND WEAKNESSES OF THE ADMINISTRATIVE SOURCE EPB (FLANDERS) TABLE 23. SPAIN: CHARACTERISTIC ELEMENTS OF THE ADMINISTRATIVE SOURCE ELECTRICITY, NATURAL GAS AND LPG SURVEYS TABLE 24. SPAIN: STRENGTHS AND WEAKNESSES OF THE ADMINISTRATIVE SOURCE ELECTRICITY, NATURAL GAS AND LPG SURVEYS TABLE 25. SPAIN: CHARACTERISTICS ELEMENTS OF IN SITU MEASUREMENT SPAHOUSEC-SECH MEASURES ELECTRICITY CONSUMPTION IN 600 HOMES TABLE 26. SPAIN: STRENGTHS AND WEAKNESSES OF IN SITU MEASUREMENT SPAHOUSEC-SECH MEASURES ELECTRICITY CONSUMPTION IN 600 HOMES TABLE 27. SWEDEN: CHARACTERISTICS ELEMENTS OF IN SITU MEASUREMENT METERING OF DOMESTIC ELECTRICITY USE AT APPARATUS LEVEL IN 400 HOUSEHOLDS... 53

5 TABLE 28. SWEDEN: STRENGTHS AND WEAKNESSES OF IN SITU MEASUREMENT METERING OF DOMESTIC ELECTRICITY USE AT APPARATUS LEVEL IN 400 HOUSEHOLDS TABLE 29. SLOVENIA: CHARACTERISTICS ELEMENTS OF THE MODEL OF ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 30. SLOVENIA: STRENGTHS AND WEAKNESSES OF THE MODEL OF ENERGY CONSUMPTION IN HOUSEHOLDS TABLE 31. FINLAND: CHARACTERISTICS ELEMENTS OF THE RAKLAMM CALCULATION MODEL FOR SPACE AND WATER HEATING TABLE 32. FINLAND: STRENGTHS AND WEAKNESSES OF OF THE RAKLAMM CALCULATION MODEL FOR SPACE AND WATER HEATING TABLE 33. UNITED KINGDOM: CHARACTERISTICS ELEMENTS OF THE BREHOMES-MODELS NATIONAL AGRREGATES OF DOMESTIC ENERGY USE TABLE 34. UNITED KINGDOM: STRENGTHS AND WEAKNESSES OF THE BREHOMES-MODELS NATIONAL AGRREGATES OF DOMESTIC ENERGY USE TABLE 35. SWITZERLAND: CHARACTERISTIC ELEMENTS OF THE MODEL ANALYSIS OF SECTORIAL ENERGY CONSUMPTION BY END-USE TABLE 36. SWITZERLAND: STRENGTHS AND WEAKNESSES OF THE MODEL ANALYSIS OF SECTORIAL ENERGY CONSUMPTION BY END-USE TABLE 37. AUSTRIA: CHARACTERISTIC ELEMENTS OF THE MODEL MATCHING THE RESULTS OF HOUSEHOLD ELECTRICITY CONSUMPTION SURVEY WITH HOUSEHOLD ENERGY CONSUMPTION SURVEY TABLE 38. AUSTRIA: STRENGTHS AND WEAKNESSES OF THE MODEL MATCHING THE RESULTS OF HOUSEHOLD ELECTRICITY CONSUMPTION SURVEY WITH HOUSEHOLD ENERGY CONSUMPTION SURVEY TABLE 39. SPAIN: DWELLING AND HOUSEHOLD FEATURES TABLE 40. SPAIN: HOUSEHOLD EQUIPMENT TABLE 41. SPAIN: AGGREGATE ENERGY CONSUMPTIONS BY ENERGY SOURCES TABLE 42. SPAIN: ENERGY CONSUMPTIONS BY SERVICES/USES AND BAY ENERGY SOURCES. 76 TABLE 43. CYPRUS: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE TABLE 44. CYPRUS: STRENGTHS AND WEAKNESSES TABLE 45. USA: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE TABLE 46. USA: STRENGTHS AND WEAKNESSES TABLE 45. GREECE: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE TABLE 46. GREECE: STRENGTHS AND WEAKNESSES TABLE 47. LATVIA: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE... 81

6 TABLE 48. LATVIA: STRENGTHS AND WEAKNESSES TABLE 49. SLOVENIA: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE TABLE 50. SLOVENIA: STRENGTHS AND WEAKNESSES TABLE 51. SPAIN: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE TABLE 52. SPAIN: STRENGTHS AND WEAKNESSES TABLE 53. AUSTRIA: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE TABLE 54. AUSTRIA: STRENGTHS AND WEAKNESSES... 88

7

8 1. INTRODUCTION The following report makes a deep analysis of those very best experiences for collecting statistics on residential energy consumption on the basis of the research performed in Reports 2 and 3. The analysis will be made by each of the main information sources considered in the project, namely: surveys, administrative sources, in situ measurements, models, and integrated approaches. In order to assess each of these categories of information sources the following criteria will be taken into account: First, what the key methodological elements which define each source as excellent are. Second, what the strengths and weaknesses found in the analyzed sources are. Third and final, the main similarities and differences found between them and the transferability degree of each statistical method, understood as the ability of being applied to other countries. 8

9 2. BEST PRACTICES BY STATISTICAL METHODS Before proceeding with the individual evaluation of each statistical method, it must be explained that surveys, administrative sources and in situ measurements have been analyzed according to the following structure: Characteristic elements. This sections includes: purpose of the source, source uses, key methodological elements, fulfillment of the best practices criteria (mandatory criteria, impartiality and objectivity, design of the survey or data collection, regular recurrence, units or subjects from which the information is extracted, regional level, effectiveness, efficiency, accuracy, reliability and quality, spreading and accessibility) and fulfillment of the task force 2008 criteria (total score and must have, nice to have, renewable and energy poverty criteria). Strengths and weaknesses; Similarities and differences. On the other hand, the statistical method model has a different and specific analysis, which is presented in the following sections: Characteristic elements This sections includes: model purpose, key methodological elements, analysis of the issues and results of the model (comprehensiveness, results reconciliation with other data, effectiveness of the model, publicity and availability of results and methodology and frequency) and fulfillment of the task force 2008 criteria (total score and must have, nice to have, renewable and energy poverty criteria). Strengths and weaknesses; Similarities and differences. The last statistical method, integrated approach, is analyzed according to the following points: Crossing purpose; Sources crossed; Variables checked; Additional information SURVEYS Seven have been the very best Surveys selected from all the countries analyzed: Survey Energy Consumption in Households (Cyprus) 9

10 Residential Energy Consumption Survey (RECS) (USA) Survey Statistics on Energy Consumption in Households (Austria) Survey Energy Consumption in Households (Greece) Survey German Residential Energy Consumption Survey (Germany) Survey Energy Consumption in Households (Portugal) Survey Statistics on Energy Consumption in Households (Bulgaria) Survey Energy Consumption in Households (Cyprus) The survey Energy Consumption in Households, implemented by the Statistical Service of Cyprus, has been chosen as the best practice in the ranking of best practices according to statistical methods, due to both the high level of accomplishment of the operational criteria established for best practices and the high level of coverage of the requirements of the TF2008. The survey data are collected by means of personal interviews in more than 3,300 households out of the 268,000 Cypriot households, which allows minimizing sampling error. The procedure of personal interviews helps to solve problems of data collection and to debug information in order to correct errors. The sample frame of reference of the survey is the Census of 2001, but it has been completed with other sources in order to correct distortions derived from temporal evolution. At the same time, all the calculations out of the data achieved in the survey have been checked with information from the Industry Department and the Electricity Authority. Nonetheless it must be pointed out that a number of problems and difficulties were encountered throughout the data collection phase. Most of the problems were related to the difficulty the respondents had on giving accurate answers to some of the variables of the questionnaire. Moreover, some questions proved to be difficult to answer due to the high technicality involved. This has resulted in a response rate equal to 83%. On the other hand this survey stands out because it differentiates between owners and tenants, and between urban and rural areas. This allows capturing the different consumption habits of households according to these relevant levels of disaggregation. This survey also excels at the coverage rate of the requirements of the Task Force 2008, so that the main variables that must be accounted for analyzing energy consumption in households are covered. Specifically, the coverage rate equals 61.8%, with a high coverage of the criteria considered as MUST HAVE (61%), as well as NICE TO HAVE (63%) and RENEWABLES (100%). The survey also collects data on insulation of dwellings, such as characteristics of the windows, walls and top floor, which allows covering partially the category of energy efficiency in dwellings. 10

11 Both on Space Heating and Space Cooling information on the months and hours of use of the systems has been collected, as well as the surface of the dwelling that is heated or cooled in the corresponding seasons, which allows the collected information being much more accurate. This survey pays special attention to the measurement of the level of penetration of renewables. So, it collects data on solar collectors specifying their type and age, on heat pumps, on solar photovoltaic panels and on wind generators. Regarding biomass, the survey conveys information on type and quantity used for heating. Hence, the Cypriot survey Energy Consumption in Households may be considered effective for measuring and determining energy consumption in households, which is its desired target. The statistical good practices of the Cypriot survey Energy Consumption in Households make it an example, which could be transferred to other countries, despite it includes some aspects proper of Cyprus, as it is the NUTs level, which is national (0) due to the small size of this nation, or the no differentiation among climatic areas, due to the homogeneity of climate in this country. 11

12 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA FULFILLEMENT OF THE BEST PRACTICES CRITERIA COMPENDIUM OF BEST PRACTICES Characteristic elements TABLE 1. CYPRUS: CHARACTERISTICS ELEMENTS OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS CHARACTERISTIC ELEMENTS OF THE SURVEY: Energy Consumption in Households (CYPRUS) Characteristic element Description PURPOSE OF THE SOURCE SOURCE USES KEY METHODOLOGICAL ELEMENTS Mandatory character for the collection of the data Impartiality and objectivity Design of the survey or data collection Regular recurrence Units or subjects from which the information is extracted Territorial signification To obtain a reliable estimate of the final energy consumption of a typical Cypriot household by end use category (space heating, water heating, space cooling, cooking, electrical appliances and lighting). This survey reaches the aimed targets with success. It provides a high quality piece of information on energy consumption in the residential sector in Cyprus. The sample size is 3,300 households, whereas in Cyprus there are 268,000 households. This relationship helps to minimize sampling errors. The sample was framed out of the Census of Population 2001, and was corrected until 2009 taking into account data from the Electricity Authority and from registers of new dwellings. The collected data serve as inputs in models that calculate final consumption by use. Data were carefully analyzed and debugged in order to minimize possible errors made during the collection process, by means of methods such as correction of extreme values or data inconsistency. For this purpose a number of different statistical programs were used. Households in rural and urban areas are differentiated. The source differentiates owners and tenants. In the data collection the intensity of use of space heating and cooling is measured, taking into account different seasons of the year, use of thermostats, and number of hours of use of the appliances. Additional information sources have been exploited when problems have arisen. For instance, in the case of electricity consumption information was requested to the Electricity Authority. This survey has a compulsory character. Publication of the information on the implemented methodology for obtaining the information: the "Development of detailed Statistics on Energy Consumption in Households (SECH project)" report. Data were collected by means of personal interviews in the selected households. The response rate achieved was 83%. Planned: every 5 years, if it is affordable. Planned next occurrence: 2015 Households. National Effectiveness The coverage rate of the criteria of Task Force 2008 is 61.8%. Efficiency The cost of the survey per interviewed household is Accuracy, reliability and quality Some mechanism for checking the data were implemented. Spreading Data are available for public knowledge on the Internet. A report on methodology and another of results are published. Accessibility Publication medium: the Internet. Total score 61.8% Must have criteria 61% Nice to have criteria 63% Renewables criteria 100% Energy poverty criteria 0% 12

13 Strengths and weaknesses TABLE 2. CYPRUS: STRENGTHS AND WEAKNESSES OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS STRENGTHS AND WEAKNESSES OF THE SURVEY: Energy Consumption in Households (CYPRUS) Strengths The sample size is high, which allows to minimize the sampling error. The sample consists of 3,300 households, whereas the total number of households in Cyprus is 268,000. The sample frame, which was defined on the basis of the census of 2001, was adapted to the temporal evolution of households. Owners and tenants are differentiated, as well as rural and urban areas, which allows to observe the different consumption habits. Weaknesses This survey does not measure energy efficiency in depth. As intensity of occupation of the dwellings is not observed, some data in this sense are not accurate enough. Whenever problems have arisen during data collection, different solution methods have been tried. The cost per individual is remarkably low. The initial aimed targets have been reached. This survey is a powerful means for measuring energy consumption in the residential sector Residential Energy Consumption Survey (RECS) (USA) This source has been valuated as the second best survey according to statistical methods. Additionally, it achieves the second highest coverage rate of the TF2008 criteria, and it is noticeable that the coverage rates within the categories NICE TO HAVE, RENEWABLES and ENERGY POVERTY equals 100%. The main purpose of this survey is the estimation of households' energy consumption by end uses, in order to improve energy efficiency in the residential sector and to meet future energy demand properly. This survey is integrated in the statistical framework of the USA and is a key piece in it; its results are checked and integrated with those of other information sources, and serve as inputs for modeling. It includes (in addition to the CATI and Mailed questionnaire methods) a Computer Assisted Personal Interview (CAPI). This method has many advantages, as it minimizes errors concerning data collection to the extent that doubts of respondents about the questions can be explained by the interviewers, which are specially trained, and the latter can check inconsistencies of answers and mend them at the moment; on the other hand, the cost of CAPIs are higher than the cost of other means for collecting answers, such as the mailed questionnaires or the telephone interviews. The questionnaire is very comprehensive and questions are very exhaustive; additionally the interviewers inspect physically the dwelling and scan the energy bills. 13

14 This survey exploits a multi-stage probability design, which ensures that the selected households represent properly the whole occupied housing units in the USA. A wide range of key variables affecting energy consumption in households is considered; factors such as household type, housing type, tenure regime, city/town/suburbs/rural area, and areas of the country are investigated in detail. Questions about energy service demand are very complete. Energy poverty receives an exhaustive treatment. The results, micro data - only to same extent of detail, according to the right for intimacy -, and information on methodology are free accessible on the Internet. Some improvements could be made, mainly related to the variables penetration of energy efficiency technologies, which are not asked in detail, and the category RENEWABLES, where the registered variables are only type of fuel and the availability of the energy source. Finally, it must be pointed out that this survey, which has a voluntary character, could present problems of social nature regarding transferability due to the exhaustive and faceto-face method of collecting the information, which includes inspections and scanning of energy invoices as well. 14

15 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA FULFILLEMENT OF THE BEST PRACTICES CRITERIA COMPENDIUM OF BEST PRACTICES Characteristic elements TABLE 3. USA: CHARACTERISTIC ELEMENTS OF THE SURVEY RESIDENTIAL ENERGY CONSUMPTION SURVEY (RECS) CHARACTERISTIC ELEMENTS OF THE SURVEY: RESIDENTIAL ENERGY CONSUMPTION SURVEY (RECS) (USA) Characteristic element PURPOSE OF THE SOURCE SOURCE USES KEY METHODOLOGICAL ELEMENTS Description The main purpose is the estimation of households' energy consumption by end uses The information is chiefly used for meeting future energy demand properly and improving efficiency and building design It is a Computer Assisted Personal Interview (CAPI) The information collected by means of the survey is combined with data from energy suppliers The type of sampling is a multi-stage area probability design; its proper application ensures that the selected sample represents the entire population of occupied housing units in the United States It differentiates by household types, housing types, tenure regime, city/town/suburbs/rural area, and areas of the country Specially trained interviewers collect energy characteristics on the housing unit, usage patterns, and household demographic and economic characteristics The interviewers measure the square footage of each housing unit, specifically the area of the housing unit that is enclosed from the weather, including exterior walls, differentiating four areas: attic, basement, garage, and rest of home The information achieved by this survey is combined with the information achieved by the Household Survey and the Rental Agent Survey, which capture energy characteristics for sampled housing units, and with the Energy Supplier Survey (ESS) This survey provide inputs to the estimation of end-use consumption through a nonlinear statistical model applied to data from the Household and Energy Supplier Surveys, which disaggregates total energy consumption into end-use components Mandatory character for the collection of the data Impartiality and objectivity Design of the survey or data collection Regular recurrence The response is not compulsory Reports on methodology are available on the Internet at Response rate: 79% Form of collecting the information: CAPI (Computer Assisted Personal Interview), CATI (Computer Assisted Telephone Interview) and Mailed Questionnaire Every 2-3 years. Next planned collection date is Units or subjects from which the information Households is extracted Territorial signification Data are significant at the national level Effectiveness The coverage rate of TF2008 criteria was 75.65%% Efficiency Accuracy, reliability and quality Spreading Accessibility Total score 75.65% Must have criteria 71% Nice to have 100% Renewables criteria 100% Energy poverty criteria Global results and micro data are accessible on the Internet The RECS and many of the U.S. Energy Information Administration (EIA) supplier surveys are integral ingredients for some of EIA's more comprehensive data products and reports, such as the Annual Energy Outlook (AEO) and Annual Energy Review (AER) Statistics, and micro data to same extent of detail, are available on the Internet at 100% 15

16 Strengths and weaknesses TABLE 4. USA: STRENGTHS AND WEAKNESSES OF THE SURVEY RESIDENTIAL ENERGY CONSUMPTION SURVEY (RECS) STRENGTHS AND WEAKNESSES OF THE SURVEY: RESIDENTIAL ENERGY CONSUMPTION SURVEY (RECS) (USA) Strengths Weaknesses It is a CAPI. In addition it includes the CATI and mailed questionnaire methods for collecting data Penetration of renewables is not registered in detail The data sources are various, which guarantees precision: the responses from Penetration of energy efficiency technologies is not the selected households, the measurements asked in detail and inspections by the interviewers, and the scanning of energy consumption bills The sampling technique allows high quality inference from sample to population The coverage rate of the criteria of Task Force 2008 is the seond higher of the analyzed surveys This survey differentiates by key variables affecting energy consumption in households such as household type, housing type, tenure regime, city/town/suburbs/rural area, and areas of the country This source forms part of a wider statistical framework, and so its results are checked and integrated with those of other information sources, and serve as inputs for modelling The questionnaire is very comprehensive of all the relevant aspects concerning energy consumption in households Information about energy service demand is asked in detail It collects information on energy poverty, and does it with a practical and direct approach, asking the households about economic difficulties to enjoy energy consumption The results, micro data (only to same extent of detail), and information on methodology are free accessible on the Internet Survey Statistics on Energy Conpsumption in Households (Austria) The survey Energy consumption in households of Austria has been selected among the best surveys regarding best practices according to statistical methods due to its high level of accomplishment of the operational criteria. In this sense this survey stands out in aspects such as efficiency, because the incurred cost per interviewed household is only 8.08 euros, 16

17 one of the lowest among all the analyzed surveys. Besides, this survey has continuity in time, which allows the data to be compared and checked with those of previous series, and at the same time observing the trends of energy consumption in Austrian households. This survey also excels in the validation and contrast of data, because a thorough analysis of them is carried out in order to minimize possible errors. The results are compared together with other statistics on energy consumption (the material input statistics, the survey on energy consumption in small establishments of the manufacturing industry and the survey on energy consumption in the service sector) regarding quantities of fuels. A new approach to data control was also adopted, compared with previous surveys, in 2004, and maintained in the following surveys. Only the individual energy sources themselves were checked for plausibility, any missing data were calculated (quantity-value pairs) and substitutions were made when necessary. Such routines of course continue to be used, with the additional step that the total of the reported energy consumption is then related to a calculated (fictitious) overall consumption. This fictitious overall consumption by the household is calculated from the data for that household, on the one hand (floor space, number of people living in the household), and applying pre-set parameters for the individual types of use (space heating, water heating, cooking, other purposes), on the other hand. The survey and the statistics of Austria on energy consumption in households have become a reference and guide for the implementation of the statistics on energy consumption in households in other countries. For instance, Romania took this survey as reference. This fact supports the plausibility that the survey and the processing of the data implemented in Austria may be extrapolated to other countries and serve as guide for other statistics, because its transferability is high. The coverage rate of the whole criteria in this survey is 65.6%, the coverage of the criteria MUST HAVE is equal to 67%, the coverage of the criteria NICE TO HAVE is equal to 50% and the coverage of the criteria RENEWABLES equals 100%. It must be also said that, despite the high level of accomplishment of the operational criteria, some aspects are not much positive. This survey is not independently developed, but it is implemented through an additional module in the Labour Force Survey, and only a fifth part of the sample is interviewed via personal interviews, while the rest is interviewed via telephone; this latter fact can worsen the precision of data, and also results in a low response rate, 60%. Additionally, this survey has evolved throughout its life with the purpose of fulfilling the needs of the Administration, and not so much in order to cover the requirements stated by the Task Force. In this sense the majority of the changes have been aimed at the improvement of the energy balance statistics, because of the additional difficulties that market liberalization meant for the processes of data collection in this field. 17

18 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA FULFILLEMENT OF THE BEST PRACTICES CRITERIA COMPENDIUM OF BEST PRACTICES Characteristic elements TABLE 5. AUSTRIA: CHARACTERISTICS ELEMENTS OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS CHARACTERISTIC ELEMENTS OF THE SURVEY: Energy Consumption in Households (AUSTRIA) Characteristic element PURPOSE OF THE SOURCE SOURCE USES KEY METHODOLOGICAL ELEMENTS Description To determine total household energy consumption To determine household appliances energy consumption To collect household energy expenditure To collect dwelling physical characteristics To collect household occupant characteristics Voluntary random sample survey stuck to the obligatory labor force survey The collected data serve as inputs in models that calculate final consumption by use. A new approach to data control was taken compared with previous surveys the first time in 2004 and continued in the following surveys Only the individual energy sources themselves were checked for plausibility, any missing data were calculated (quantity-value pairs) and substitutions were made if necessary The reported energy consumption is then related to a calculated (fictitious) overall consumption. The grossing up is done with the criteria of labor force survey. The results are compared together with other statistics on energy consumption (the material input statistics, the sample survey on energy consumption of small establishments of the manufacturing industry and the sample survey on energy consumption of the service sector) with the quantities of fuels available Mandatory character for the collection of the data This survey is not compulsory. Impartiality and objectivity Publication of the information on the implemented methodology for obtaining the information: "Energy Consumption of Households" Standard documentation meta information, May 2009 Design of the survey or data collection Regular recurrence Households. Units or subjects from which the information is extracted Territorial signification NUTs 2 The data are collected by means of Computer Assisted Personal Interviews and Computer Assisted Telephone Interview. The response rate was 60%. Planned: every 2 years Planned next occurrence: 2012 Effectiveness The coverage rate of the criteria of Task Force 2008 is 65.6%. Efficiency The cost of the survey per interviewed household is Accuracy, reliability and quality The results are compared together with other statistics on energy consumption (the material input statistics, the sample survey on energy consumption of small establishments of the manufacturing industry and the sample survey on energy consumption of the service sector) with the quantities of fuels available Spreading Data are available for public knowledge on the Internet. A report on methodology and another of results are published. Accessibility Total score 65,6% Must have criteria 67% Nice to have 50% Renewables criteria 100% Energy poverty 0% Publication medium: the Internet. 18

19 Strengths and weaknesses TABLE 6. AUSTRIA: STRENGTHS AND WEAKNESSES OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS STRENGTHS AND WEAKNESSES OF THE SURVEY: Energy Consumption in Households (AUSTRIA) Strengths Weaknesses This survey gets a high valuation according operational criteria. The response rate is only 60%, among the lowest of all the analyzed surveys The frequency of the survey is biannual, The survey neither differentiates by climate zones nor which allows comparability of data among by tenure regime. This may result in lack of accuracy. different series and observing the trends of energy consumption in households. All the data are checked and contrasted with those of previous series. Besides, they are validated with data coming from other sources of information on energy consumption. This results in high quality data. Possible errors in estimates are evaluated. A confidence interval of 95% is set for the estimates. The estimation process allows obtaining consumption by use as well as by floor surface and number of occupants of the dwelling Survey Energy Consumption in Households (Greece) The survey Energy Consumption in Households by Statistics of Greece (ELSTAT) has been selected as best practice according to statistical methods mainly on account of its high level of accomplishment of the criteria of the Task Force In fact the coverage rate of those requirements is 77,5%, the highest among all the analyzed surveys. This survey excels at the coverage rate of the criteria MUST HAVE, which is 77%. It is in the group of criteria NICE TO HAVE where its level of accomplishment is higher, instead, with a coverage rate equal to 85%. The coverage of the criteria RENEWABLES is 100%. In addition to that, the survey of Greece is noticeably innovative regarding achievement of information on energy consumption, and this feature has also contributed to its selection as best practice. The survey takes into account the availability of shading systems, ceiling/floor fan, indoor atrium, sunspace (bioclimatic greenhouse), green roof, automatic control system for energy saving, besides the criterion of energy service demand: intensity of use of thermostats in heating and cooling. Apart from that income is provided by a synchronous survey on the households budget planning. The sampling technique of this survey has been developed with signification for all the regional levels, although the cost is higher than in the cases of the two surveys preceding it 19

20 in the ranking of best practices, and the response rate is lower, 60% (the lowest value in response rate together with Austria). In spite of all its positive characteristics, it must be pointed out that this survey is still in the phase of implementation and so all the information about it is provisional and could change before the final results are published by the middle of Then it will be obliged to do a revision of the analysis of this source. 20

21 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA FULFILLEMENT OF THE BEST PRACTICES CRITERIA COMPENDIUM OF BEST PRACTICES Characteristic elements TABLE 7. GREECE: CHARACTERISTICS ELEMENTS OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS CHARACTERISTIC ELEMENTS OF THE SURVEY: Energy Consumption in Households (GREECE) Characteristic element PURPOSE OF THE SOURCE Description The main purpose is measuring energy consumption in Greek households. SOURCE USES KEY METHODOLOGICAL ELEMENTS Mandatory character for the collection of the data Impartiality and objectivity Design of the survey or data collection Regular recurrence Units or subjects from which the information is extracted Territorial signification This survey is successful in relation to the achievement of its aimed targets. It provides high quality information on energy consumption in the residential sector in Greece. Sample size is 3,500 (households), whereas the corresponding total number of households in Greece is 4,371,000; this relationship allows to minimize possible sampling errors. Intensity of use of space heating and cooling is measured, differentiating among seasons and taking into account the use of thermostats and the number of hours of work of the devices. Compulsory. Publication of the data, report of results and report on methodology are planned for Personal interviews in the selected households. The response rate was 60%. It is a pilot experience within the SECH project, and its implementation started in 2011 and will finish in For this reason its future occurrence is not decided. Households. All the regional levels in Greece. Effectiveness The coverage rate of the criteria of the Task Force 2008 is 60.2%. Efficiency Accuracy, reliability and quality Spreading Accessibility Total score 77,5% Must have criteria 77% Nice to have criteria 85% Renewables criteria 100% Energy poverty criteria 0% Sample cost per interviewed household is 67,14. Throughout the process some mechanisms for checking data were implemented in order to improve reliability. A report of methodology will be included in the quality report of the survey and will be published on the website of ELSTAT by mid The results will be disseminated via the website of ELSTAT ( by mid

22 Strengths and weaknesses TABLE 8. GREECE: STRENGTHS AND WEAKNESSES OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS STRENGTHS AND WEAKNESSES OF THE SURVEY: Energy Consumption in Households (GREECE) Strengths Weaknesses The ratio of sample size to population size is high, 3,500 to 4,371,000 households, which helps to minimize sampling error. The coverage rate of the criteria of the Task Force 2008 is the highest among all the analyzed surveys. It is remarkable the value of the coverage rate of the criteria MUST TO HAVE, 77%, the most important one. Data in winter and summer are differentiated, as well as the moments of the day when space heating and cooling are used. This allows data showing the different intensity of demand for these two end uses. It is also relevant the measurement of intensity of use via thermostats. No continuity of this experience would result in impossibility of analyzing trends of energy consumption in households. As this survey is being currently implemented, the achieved results are not definitive. The cost per interviewed household is the highest among the surveys selected as best practices according to statistical methods. Neither owners and tenants nor rural and urban areas are differentiated. This prevents inspecting the different habits of consumption regarding these variables Survey German Residential Energy Consumption Survey (Germany) In spite of its low coverage rate of the criteria of the Task Force 2008, 58%, in relation to the other surveys considered as best practices according to statistical methods, the German Residential Energy Consumption Survey does a thorough job regarding collection of data on energy consumption. Thus, a main feature of this survey consists in the consideration of the major problems and difficulties that could arise during its development, finding solutions for most of them. Households are stratified by climatic areas with the purpose of estimating current consumption taking into account average temperatures. The household-specific climate conditions were obtained by a grid of climate stations operated by Deutscher Wetterdienst, and geographically interpolated into the households places of residence. This enables to estimate not only the purchases of energy by source but the corresponding current consumption as well. In the same way data provided with information on invoicing have been corrected. Another striking aspect of this survey consists in the fact that the extrapolation was stratified by region and type of building, or in exceptional cases by household size. Econometric discrete choice models were used to derive a weighting scheme to overcome possible problems with self-selection effects in the data. Self-selection might occur, if households that are hardly aware of their energy consumption are also less 22

23 diligent with keeping their energy bills, and are therefore unable to quantify their energy consumption. In consequence, the sample would consist systematically of households with a low consumption, and the true residential energy consumption would be underestimated. The derived weighting scheme aims at accounting for such potential data problems. This survey especially emphasizes the measurement of energy consumption via renewable, and for this purpose a parallel collection of data is made by widening the sample. As it has been commented, the German Residential Energy Survey doesn t have a high level of accomplishment of the criteria of the Task Force 2008, so to that extent it is less transferable to other countries than other analyzed surveys, because some variables have not been considered when estimating energy consumption in households. Despite of this fact, this survey includes many statistical characteristics that would be desirable to find in the statistics which the different States implement. Thus, it is the only one that differentiates between purchases of energy sources and the corresponding current consumptions, correcting via climatic conditions. In addition to that, this survey may be very useful for those entities interested in improving their statistics on energy consumption of renewables in households, because of the remarkable job done in this field. 23

24 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA FULFILLEMENT OF THE BEST PRACTICES CRITERIA COMPENDIUM OF BEST PRACTICES Characteristic elements TABLE 9. GERMANY: CHARACTERISTICS ELEMENTS OF SURVEY GERMAN RESIDENTIAL ENERGY CONSUMPTION CHARACTERISTIC ELEMENTS OF THE SURVEY: German Residential Energy Consumption Survey (Germany) Characteristic element PURPOSE OF THE SOURCE Description To determine total household energy consumption To determine household appliances energy consumption To collect household appliances diffusion To collect household energy expenditure To collect dwelling physical characteristics To collect household occupant characteristics SOURCE USES KEY METHODOLOGICAL ELEMENTS Data are validated taking into account data from invoices of 100 households. Temperatures related to the locations of the dwellings are determined by climatic areas. The data achieved refer both to consumption and purchases of energy by source. The sample estimates are extrapolated to derive consumption figures for the entire population of private households in Germany. This survey was improved for enabling it to measure more accurately energy consumption of renewables. It distinguishes between energy consumption proper of the dwelling and transport energy consumption of the household. Confidence ranges are established in order to ensure that estimates are valid for the entire population. Mandatory character for the collection of the data Impartiality and objectivity Design of the survey or data collection Regular recurrence Units or subjects from which the information is extracted Territorial signification This survey is not compulsory. Publication of the information on the implemented methodology for obtaining the information: "The German Residential Energy Consumption Survey " report published by Statistics Germany. Data were collected by means of Computer Assisted Telephone Interview. The response average was 70%. Every 2-3 years. Next planned collection date is Households. The sample is designed as a panel of 10,000 households out of a total number of 39,311,000 households in Germany. National. Effectiveness The coverage rate of the criteria of the Task Force 2008 is 58.2%. Efficiency Data are validated taking into account data from invoices of 100 households. Accuracy, reliability and quality Automated checks are performed during data collection in order to ensure reliability. Spreading A methodological report and other of results are published. Accessibility The report of results is available on the web site of Statistics Germany Total score 58% Must have criteria 60% Nice to have criteria 35% Renewables criteria 100% Energy poverty criteria 0% 24

25 Strengths and weaknesses TABLE 10. GERMANY: STRENGTHS AND WEAKNESSES OF SURVEY GERMAN RESIDENTIAL ENERGY CONSUMPTION STRENGTHS AND WEAKNESSES OF THE SURVEY: German Residential Energy Consumption Survey (Germany) Strengths Weaknesses A thorough analysis of possible problems concerning the survey is carried out in order to provide with solutions and improve reliability. Households are stratified by climatic areas with the purpose of estimating current consumption taking into account average temperatures. This enables the results to measure not only the purchases of energy by source but the corresponding current consumption as well. Sample is designed by means of a panel of households. This facilitates the correction of possible sampling errors. Data are confronted with others from invoices of 100 households, in order to check accuracy of responses. Households with low energy consumption are only surveyed presuming that households with high energy consumption are unaware of information related to their consumption because their higher incomes. This supposition is taken into account when making inference for the national population. A confidence range is estimated for ensuring that results are representative. The continuity and high frequency of this survey allows estimating trends of energy consumption in households. The sample is widened in order to catch more reliably consumption of renewables. This survey doesn t analyze in depth energy efficiency. Intensity of occupation is not considered, so some results are not as accurate as desirable. This survey has the lowest coverage rate of the criteria of the Task Force 2008 among the surveys selected as best practices according to statistical methods Survey Energy Consumption in Households (Portugal) The Portuguese survey Energy Consumption in Households has been selected as a statistical best practice mainly due to the sampling techniques implemented. Thus, in view of the analysis of quality of the data, demanding for them coefficients of variation below 20%, it may be considered that the information extracted from the survey fairly reflects energy consumption in the residential sector. In addition to that, this survey has territorial signification at NUTs 2 level, it has a high response rate, 86.7%, and it differentiates among mainly urban areas, moderately urban areas and mainly rural areas, which allows inspecting the corresponding different consumption habits according to this classification. In spite of this level of disaggregation the cost of this survey is lower than in the case of the survey of Greece, that is, a low cost. It must be mentioned that this survey not only analyzes energy consumption in dwellings, but it estimates transport energy consumption in households throughout the year, because it is considered as consumption proper of them. The coverage rate of the criteria of the Task Force 2008 is 59.1%. Although it may be pointed out that this coverage is not among the highest ones of the surveys selected as best practices according to statistical methods, it is one of the highest considering all the 25

26 surveys of all the countries, and besides it covers well the type of fuel by different end uses (though there are not collected data on characteristics of heating systems, water heating ) and especially the criteria of energy efficiency concerning labeling of equipment by appliance type and energy efficiency of lamps. It also offers as novelty the collection of data on heating/cooling per unit of surface area (m 2 ); number of heating system; number of using/week(number of hours using/week); day period for using (all day, only night; only day). All the data achieved by means of this survey are validated, and crosscutting with the annual information from the energy suppliers is performed. 26

27 Characteristic elements TABLE 11. PORTUGAL: CHARACTERISTICS ELEMENTS OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS 27

28 Strengths and weaknesses TABLE 12. PORTUGAL: STRENGTHS AND WEAKNESSES OF SURVEY ENERGY CONSUMPTION IN HOUSEHOLDS STRENGTHS AND WEAKNESSES OF THE SURVEY: Energy consumption in Households (PORTUGAL) Strengths The aimed targets have been reached. This survey is a powerful means for measuring energy consumption in the residential sector. The analysis of energy consumption goes beyond the consumption in dwellings, as consumption of transport in households is also analyzed. Sample size is big, 7,468,000 households, whereas there are 3,932,010 households in Portugal. This helps to minimize sampling error. Mainly urban area, moderately urban area and mainly rural area are differentiated, which allows to measure the different consumption habits in regard with these three different types of location. The analysis of data quality performed, which only admits those with a coefficient of variation below 20%, and the analysis of possible sampling errors, allows to presume that the statistics fairly show energy consumption in the residential sector. Weaknesses Ownership and tenancy are not differentiated. Thus, differences in consumption habits due to this distinction cannot be measured, though main and secondary dwellings are distinguished. Intensity of consumption by end use is not measured, which prevents from estimating adequately the future trends of energy consumption in the residential sector. This survey is not foreseen to be replicated. Climatic areas are not differentiated. This prevents from measuring different consumption habits by climatic area. It has the lowest coverage rate in renewables among the seven surveys considered Best Practices Survey Statistics on Energy Conpsumption in Households (Bulgaria) The survey Statistics on Energy Consumption in Households of Bulgaria has been the third survey selected as best practice according to this type of statistical method. This survey aims chiefly at estimating energy consumption in households, mainly by energy source, and proves to be highly effective because it reaches a high level of accomplishment of these criteria of the Task Force The survey developed by the National Statistical Institute of Bulgaria follows a methodology that allows getting reliable results, because sampling techniques and debugging processes are remarkable. The response rate is 99.4%. Sampling errors for some variables are calculated setting a confidence interval of 95%, as a way of checking the validity of the data. Besides, data were confronted with information provided by electricity suppliers. The high level of accomplishment of the criteria of the Task Force 2008, whose coverage rate is 67,5%, must be also highlighted, as its ranking is 3 in relation to this rate among all the surveys covered in this research. This figure mainly derives from the high coverage rate of the criteria considered as MUST HAVE, NICE TO HAVE AND RENEWABLES, which are 70%, 63% and 70%, respectively. Other remarkable features consist in the differentiation of data between summer and winter, as well as the estimation of space heating and space cooling at the different moments of the day, which allows revealing the different intensities 28

29 of energy demand according to these end uses. These results are achieved by means of specific questions in the questionnaire which deal with these types of details. A disadvantage of the Bulgarian survey lies in the unavailability of information about its cost, which makes impossible to assess its results regarding efficiency. This survey is remarkably able of being transferred to other countries that need to meet their energy consumption according to the energy sources used, because the survey developed by Bulgaria achieves this target with high precision. On the opposite side, this survey can be improved, as it does not distinguish among climatic areas, which may constitute a problem regarding transferability (even though this absence suits well with the homogeneous geothermal conditions of Bulgaria). 29

30 Characteristic elements TABLE 13. BULGARIA: CHARACTERISTICS ELEMENTS OF SURVEY STATISTICS ON ENERGY CONSUMPTION IN HOUSEHOLDS 30

31 Strengths and weaknesses TABLE 14. BULGARIA: STRENGTHS AND WEAKNESSES OF SURVEY STATISTICS ON ENERGY CONSUMPTION IN HOUSEHOLDS Similarities and differences found among the surveys Similarities: The seven selected surveys show some similarities, especially those developed inside the SECH project. The surveys implemented in Cyprus, Austria, Bulgaria, Greece and Portugal are similar especially regarding the variables taken into account for measuring energy consumption in households. This five surveys are also very similar in other aspects such as frequency and continuity, as they don t have a definite temporal continuity or their frequency is relatively low. One of the main common features of the seven analyzed surveys is the high level of accomplishment of the criteria of the Task Force of All of them have a high coverage of the MUST HAVE criteria (at least, 60%) and, except two cases (Portugal and Bulgaria), all of them have a 100% of renewables criteria coverage. However the item Energy Poverty is only included in the case of USA. They are also very similar regarding energy consumption by commodities, and especial attention to the measurement of renewable energy consumption is paid in the surveys of Cyprus, Greece, USA and Bulgaria. Another common feature of four of these surveys is the low cost corresponding to each interviewed household because, though it differs among them, it is relatively low compared with those of the surveys implemented in the rest of the countries analyzed. 31

32 It is also a common element the fact that the sizes of the selected samples have been in all the cases big enough to minimize sampling errors, and it is remarkable how they achieve with success their proposed targets, contrasting data with other sources or taking into consideration possible errors. Differences: Regarding the differences that can be observed among the selected surveys, the most striking case is the survey of Germany, which notably differs from the course followed by the others. These dissimilarities are mainly due to the fact that this survey don t belong to the SECH project and as a consequence it has not followed certain guidelines during its design and development. So the German survey has certain characteristics that are not present in the rest and vice versa. For instance, the survey of Germany is the only one continuous in time and with a low frequency, which allows the selected sample to be a panel, unlike the rest of cases. Additionally, the survey of USA may be considered particular, due to the exhaustive character of the questionnaire and inspections in the data collection process. There are some characteristics that differ by groups of surveys. For instance, it can be seen that in the Cypriot, the American and the Portuguese surveys the selected households are differentiated by level of urbanization of the residence area, which is not considered in the rest of surveys. On the other hand, USA, Portugal and Germany have taken into account that energy consumption in households should comprise data on transport consumption ADMINISTRATIVE SOURCES Before proceeding with the evaluation of the administrative sources, it must be taken into account that these are information sources which, in the majority of cases, serve to different purposes that are more global than the specific target of getting data on energy consumption in the residential sector. For that reason, it must be highlighted that the administrative sources don t get in general high values of the coverage rate of the requirements of the TF2008, because their purposes, in general, are not fulfilling those requirements, but it rather are to serve as bases for the sampling design of the ad hoc surveys that intend to achieve data on energy consumption in households, to serve as inputs in models that calculate energy consumption by uses, or to serve as sources for checking and validation of results achieved by means of whatever source exploited for getting information on energy consumption in households. Five have been the Administrative Sources selected from all the countries analyzed: EAP (energy advice procedure) data and EPC (energy performance certificate) data (made in Brussels, Flanders and Wallonia). Belgium. Energy Label of buildings database. Netherlands. Client files from energy companies. Netherlands. 32

33 Electricity, Natural Gas and LPG surveys EPB (energy performance of buildings) (Flanders). Belgium The fifth source, EPB (energy performance of buildings) (Flanders), Belgium, is number six best administrative sources ranking according to statistical methods, and has been included because of its relationship, similarities and differences, with the first one, and its complementary character to that source EAP (energy advice procedure) data and EPC (energy performance certificate) data (made in Brussels, Flanders and Wallonia), Belgium. In the following sections the characteristic elements of each statistic, its strengths and weaknesses and the similarities and differences found among them as well as an analysis of the ability of each one to be transferred to other countries will be analyzed EAP (energy advice procedure) data and EPC (energy performance certificate) data (Belgium) The administrative source Energy Advice Procedure (EAP) data and Energy Performance Certificate (EPC) data of Belgium has been selected as the first best practice according to the statistical method of its category. The selection of this source is due mainly because of the importance that the data collected by means of this methodology have in energy policy and, specifically, in the statistics on energy consumption in the residential sector. The purposes of this administrative source are, on one hand, the achievement of information about the characteristics of dwellings related to energy, and, on the other hand, providing an energy label or certificate of energy efficiency for the same dwellings, with a valuation concerning this subject. So, although this administrative source has a coverage rate equal to 28% regarding the TF2008, it must be emphasized the importance that this 28% of the criteria achieved has in relation to data on energy consumption in households, because it allows to have an updated housing census by ownership type and type of housing according to the insulation, the heating system, the hot water system and the renewable energy production system. This methodology basically consists in households resorting to external advisors. After the inspection the applicant receives a certificate of the energy performance of the residence using an indicator (energy score) and recommendations to improve the energy performance of the residence in order to improve energy efficient living. This method cannot be considered innovative, though it has the advantage of relieving the Administration of procedural burdens. In this sense it is efficient for the Administration. This methodology must be implemented during several years in order to be effective for energy policy purposes and. It is easily transferable, as it does not involve major efforts for the Administration; it relies mainly in the private activity. 33

34 Characteristic elements TABLE 15. BELGIUM: CHARACTERISTICS ELEMENTS OF ADMINISTRATIVE SOURCE EAP DATA AND EPC DATA 34

35 35

36 Strengths and weaknesses TABLE 16. BELGIUM: STRENGTHS AND WEAKNESSES OF ADMINISTRATIVE SOURCE EAP DATA AND EPC DATA Energy Label of buildings database (Netherlands) Energy label of buildings data base of the Netherlands is number two in the ranking of best practices according to statistical methods in the category of administrative sources. This is an administrative source which matches very well with the requirements of information on energy consumption in households in order to develop an appropriate energy policy. Both this source and the Belgium one previously commented, help to set the characteristics of energy efficiency of dwellings and aim at providing with a database of energy labels (A-G) and related information for every building that has been assigned an energy label. Data are collected in situ by experts, collecting information from numerous variables influencing energy consumption. Nevertheless, there is no information provided about costs, so to that extent an analysis of efficiency is not possible. In practice, because there have until 2012 been no sanctions, only a small (but growing) fraction of owner-occupied buildings have been energy-labelled. However, for rented buildings (households in this case), the fraction with an energy label is approaching 50%.The sample population, though relatively large in number is not strictly representative and has so far not been used for reporting on more than energy labels by Statistics Netherlands. It would be very interesting to have this information in all the countries, as it is the case of Belgium. So the transferability of this method should be promoted. The data provided by these administrative sources have a greater scope, in economic and environmental aspects, than the mere achievement of data on energy consumption in households. 36

37 Characteristic elements TABLE 17. NETHERLANDS: CHARACTERISTICS ELEMENTS OF ADMINISTRATIVE SOURCE ENERGY LABEL OF BUILDINGS DATABASE 37

38 Strengths and weaknesses TABLE 18. NETHERLANDS: STRENGTHS AND WEAKNESSES OF ADMINISTRATIVE SOURCE ENERGY LABEL OF BUILDINGS DATABASE Client files from energy companies (Netherlands) Again a Dutch administrative source, Client files from energy companies, is selected as best practice, the third in the ranking according to statistical methods in this category. In this administrative source the suppliers are the respondents, and the objective is to determine the average gas and electricity use of households on a low regional level. The methodology consists in combining information from different secondary sources: the specific combination of information sources is capable of generating important synergies for the civil service. It uses files with client information of energy companies. The client files are linked with a register of dwellings and a register of persons to identify the approximately 7.3 million households. The information achieved is exploited in the Dutch survey Home, which objective is to give insight in the average gas and electricity use of households in the Netherlands and the parameters that influence that use. The survey Home is the seventh best one in the ranking of best practices according to statistical methods in the category of surveys. It is an effective methodology, because the secondary sources of information are not of poor quality. However, no information is provided about the costs of this procedure. To that extent, an efficiency analysis cannot be carried out. An advantage of this administrative source lies in its easy transferability to other countries. Data related to lighting and gas consumption in households are contrasted with information from suppliers. 38

39 Characteristic elements TABLE 19. NETHERLANDS: CHARACTERISTICS ELEMENTS OF ADMINISTRATIVE SOURCE CLIENT FILES FROM ENERGY COMPANIES 39

40 Strengths and weaknesses TABLE 20. NETHERLANDS: STRENGTHS AND WEAKNESSES OF ADMINISTRATIVE SOURCE CLIENT FILES FROM ENERGY COMPANIES EPB (Flanders) (Belgium) The aim of this administrative source is the compilation of information on energy performance of all houses built since 01/01/2006, in order to ensure that they achieve a minimum performance level, which is expected to be more demanding according to the temporal evolution of technological, economic and environmental issues. Specifically, it covers new buildings, renovations and reconstructions, from the beginning of 2006 on, and penetration of renewable, and has a compulsory character. Thus, this statistical source is a valuable instrument of energy policy, but it has some weaknesses. Perhaps the most remarkable one lies in the fact that the EPB declaration is provided directly by the respondents and not by means of physical inspection by the authorities; this may result in a loss of precision of this source. The purpose of ensuring a minimum level of energy efficiency of buildings may as well lead to a non exhaustive or demanding measurement of the variables concerned; however, in this sense it must be taken into account that this minimum level is expected to increase alongside temporal evolution. The coverage rate of the criteria of TF2008 low, although this source achieves a 60% of coverage of the criteria related to the category RENEWABLES. The category NICE TO HAVE 40

41 is not covered (neither is ENERGY POVERTY). Many relevant factors to energy consumption in households are not analyzed, such as end uses or socioeconomic variables. Finally, it must be mentioned that data collection is continuous and fluent, and reports on results and methodology are available on the Internet. 41

42 Characteristic elements TABLE 21. BELGIUM: CHARACTERISTIC ELEMENTS OF THE ADMINISTRATIVE SOURCE EPB (FLANDERS) 42

43 Strengths and weaknesses TABLE 22. BELGIUM: STRENGTHS AND WEAKNESSES OF THE ADMINISTRATIVE SOURCE EPB (FLANDERS) Electricity, Natural Gas and LPG surveys (Spain) These surveys are administrative sources, namely censuses, which collect information from the suppliers about electricity, LPG and natural gas consumption broken down by sectors, among which the residential sector is included. The variables observed are very few regarding energy consumption in households, but they are essential and basic for the statistical information system, despite the fact that a lot of key factors influencing energy consumption in the residential sector are not covered by these sources. In these sense the coverage rate of the criteria of TF2008 is only 7.8%, and all the criteria covered pertain to the category MUST HAVE, whose coverage rate is 9.29%. The observed variables are: number of customers, type of energy commodity, quantities of energy commodity used by type, and expenditure of energy commodity by type. The outputs of these administrative sources have a very primary character, and serve as inputs to many other statistical sources on energy consumption. 43

44 The Electricity, Natural Gas and LPG surveys have a compulsory character, and the collection of data is routine and simple. They have been implemented since many decades ago, and have a stable character. Suppliers must submit the questionnaires annually to the Administration via mail, or fax. Reports on results and methodology are available on the Internet, and the territorial signification of these statistics is NUTs 3. In summary, these administrative sources can be considered as a milestone within the statistical framework on energy consumption in the residential sector, in spite of the fact that they do not cover many factors relevant to energy consumption in households. 44

45 Characteristic elements TABLE 23. SPAIN: CHARACTERISTIC ELEMENTS OF THE ADMINISTRATIVE SOURCE ELECTRICITY, NATURAL GAS AND LPG SURVEYS 45

46 Strengths and weaknesses TABLE 24. SPAIN: STRENGTHS AND WEAKNESSES OF THE ADMINISTRATIVE SOURCE ELECTRICITY, NATURAL GAS AND LPG SURVEYS Similarities and differences found among the administrative sources The first two administrative sources presented, the EAP (Energy Advice Procedure) data and EPC (Energy Performance Certificate) data (Belgium) and the Energy Label of Building Database (Netherlands) are of a very similar nature. Both of them aim mainly at providing an energy label to every dwelling in the property or rental markets. The major difference between them lies in the internal or external character of the audits. In the Belgium source data are collected by means of external audits, whereas in the Dutch source the NL Agency of the Ministry of Economic Affairs, Agriculture, and Innovation is the responsible for data collection. So, the Belgium source is more affordable for the Administration and the Dutch source more expensive for the Government, though the results and their reliability should be taken into account too. These two sources presented first substantially differ from the third source, Client Files from Energy Companies (Netherlands), because of their different purposes. This third source tries to achieve information directly on energy consumption in households, whereas the former two ones try to achieve information specifically on energy efficiency of dwellings. 46

47 Another important difference consists in the fact that the source Client Files from Energy Companies (Netherlands) collects data from secondary sources, whilst the sources EAP (Energy Advice Procedure) data and EPC (Energy Performance Certificate) data (Belgium) and the Energy Label of Building Database (Netherlands) collect data from primary sources. In this sense Client Files from Energy Companies (Netherlands) is easier to implement. The fourth source, the EPB (Energy Performance of Buildings) (Flanders)(Belgium), is related to energy efficiency in buildings, as the EAP (Energy Advice Procedure) data and EPC (Energy Performance Certificate) data (Belgium) and the Energy Label of Building Database (Netherlands), but its ultimate purpose is different, because it serves for ensuring a minimal level of energy efficiency in buildings. In addition, in the EPB (Energy Performance of Buildings) (Flanders)(Belgium), data are provided directly by the respondents, and not by means of an audit, which may result in a lack of precision. This is the most important difference between this source and the other first two. On the other hand the EPB is also relatively recent, as the two first selected sources. Analogously, the fifth selected administrative source, Electricity, Natural Gas and LPG surveys (Spain) is very similar to the third selected administrative source, Client Files from Energy Companies (Netherlands). Both collect data from suppliers on electricity and gas consumption in the residential sector. The main difference lies in the specialization in the residential sector of the source Client Files from Energy Companies (Netherlands), whereas the Spanish source has a more general target, the estimation of electricity, LPG and natural gas consumption broken down by sectors in all the national economy. For that reason, the results of the source Client Files from Energy Companies (Netherlands) are richer regarding energy consumption in households, mainly due to the use it does of official registers of dwellings and persons IN SITU MEASUREMENTS Only three countries have provided information about in situ measurements. Although other countries, specifically five, make reference in their different methodologies to the use of this type of method, they have not sent any information with respect to this. Among the countries that have reported information, the methods SPAHOUSEC-SECH Project measures electricity consumption in 600 homes of Spain and Metering of domestic electricity use at apparatus level in 400 households of Sweden have been selected as best practices SPAHOUSEC - SECH Project measures electricity consumption in 600 homes (Spain) As it has been mentioned, the Spanish in situ measurement has been selected as the best practice among all the in situ measurements analyzed. It is remarkable the wide perspective adopted on the different factors that influence electricity consumption in dwellings. In this sense in the sample selection the variables climate zone, type of dwelling, 47

48 seasons, working days and holidays and types of electrical appliance have been taken into account. Moreover, the Spanish in situ measurement SPAHOUSEC-SECH Project measures electricity consumption in 600 homes goes a step forward and collect data from questionnaires aimed at the selected households in order to measure accurately the consumption associated to services or uses. Besides, it collects data from the electricity bills provided by the owners of the selected dwellings. In order to take the measurements, 600 electricity consumption measurer equipment units were used differentiating type of dwelling and climate zone (six in total), and electricity consumption register equipment was installed. This equipment is more powerful than the aforementioned (measurer equipment) and is connected to the main switchboard of the household. It provides enough information by taking hourly measurement during a determinate period. Additionally, the register equipment can store information hour by hour; so that the real load curves can be obtained, being additionally very useful for aspects such as the measurement of standby and/or the peak demands. The measurement equipment was directly obtained for the development of the project and the supplier company assured, through certificate, both the fulfillment of EC normative and the calibration of all the equipment. The electricity consumption measurer equipment was located in the plugs of the electrical installation of the households where the equipment to be measured was later connected. Each technician was provided with 10 measurer equipment units, with the objective of taking measures of a household each week. The measurement equipment provided information on the electricity consumption (kwh) along the period of measurements as well as the time of operation of the measurement equipment. In order to assure the measurements in working days and festivities, the measurement equipment was installed for 4 consecutive days in each household, mainly from Thursdays to Sundays. The electricity consumption register equipment units were connected to the main switchboard of the households, in order to obtain hourly consumptions, providing hourly electricity consumption curves during 10 months. These curves were later used for contrasting peak demands and the standby. In addition to that, access to the Service for Information to the Citizen of IDAE (the responsible organization of the project) has been provided for every household selected in the sample in order to solve doubts and facilitate participation. Information from model consumption curves previously available from other Spanish projects has also been used. The use of meter points itself is a basic method of achieving information on electricity consumption, but the whole process implemented to carry out this in situ measurement points to excellence. The electricity equipment items, whose consumption was measured, whenever the household had such equipment, were the following ones: 48

49 Electrical service of heating: reversible and non-reversible heat pumps, electrical heaters, electrical convectors, electrical radiators and electrical boilers. Electrical service of water heating: electrical heaters of water. Space cooling: air conditioning and reversible heat pumps Cookers: electrical; glass ceramic hob and induction. Household electrical appliances: refrigerators, freezers, washing machines, washing machines-dryers, dishwashers, TVs, dryers, ovens, PCs and rest of electrical equipment. In order to take the measurements, 600 electricity consumption measurer equipment units were used, with the following characteristics: Consumption measurement in real time in watts-hours. Memory for the overall costs and energy consumed over the period chosen for measurements. Information on connection and time of operation. AC Voltage: 230V. Frequency: 50 Hz. 4 Digits (up to 9999 Watts-hours). Precision: deviation < ±5%. Consumption measurement capacity up to Watts. Throughout the measurement phase, some quality control procedures were implemented, at the stage of field research and at the stage of treatment of preliminary results. Once the field research was finished, all the information obtained together with the questionnaire was integrated and processed. The aforementioned procedure was accompanied by a filtering process through a quality control of the preliminary results. This was developed through the design of a specific software programme for automated information analyses. This Spanish statistical method achieves with success its main targets, though information about penetration of energy efficiency technologies and renewable is neglected. These two latter faults could be mended in future without great additional effort, due to the wide range of means already used. The cost per observed household is 115, which is not very high in relation of the amount of information collected. In this sense this in situ measurement cannot be considered inefficient. The Project itself has been pioneer in Spain and in some aspects, such as the measurement of the standby, in Europe. The methodology of the statistical source here analyzed is capable of being transferred to other countries. Its monetary cost is not low, but the low ratio sample size to population size 49

50 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA FULFILLEMENT OF THE BEST PRACTICES CRITERIA COMPENDIUM OF BEST PRACTICES and the accuracy, reliability and quality of the results, offset that undesirable characteristic nonetheless Characteristic elements TABLE 25. SPAIN: CHARACTERISTICS ELEMENTS OF IN SITU MEASUREMENT SPAHOUSEC-SECH MEASURES ELECTRICITY CONSUMPTION IN 600 HOMES CHARACTERISTIC ELEMENTS OF THE IN SITU MEASUREMENT: SPAHOUSEC-SECH MEASURES ELECTRICITY CONSUMPTION IN 600 HOMES (SPAIN) Characteristic element PURPOSE OF THE SOURCE SOURCE USES KEY METHODOLOGICAL ELEMENTS Description To determine the consumption of electrical equipment and services of Spanish households by "in situ" measurements of the different appliances. It is a complement belonging to the SPAHOUSEC-SECH project, project which intends to determine energy consumption in households at a global level and also segmented and systematized according to kinds of dwellings, climate zones, temporal period, types of services and types of applications or uses, Three relevant climate zones are differentiated. Two types of dwellings are considered according to the kind of building: singlefamily houses or blocks of flats. Three seasons are regarded: winter, summer and spring-autumn. Working days and holidays are distinguished. Twenty two types of electrical appliances are covered. An additional questionnaire on electrical equipment and data on consumption is sent to the households in the sample. General standby consumption is estimated. Electricity consumption bills are collected. Both a bottom-up and a top-down approach are performed. Quality control on preliminary results is carried out. Mandatory character for the collection of the data It is not compulsory. Impartiality and objectivity Design of the survey or data collection Regular recurrence The report on methodology is available on the Internet. The response rate achieved is 100% (substituting households in the sample whenever measurement is not possible). Data are collected by means of individual electricity consumption measurement equipment, questionnaires and electricity bills. Probably every 4 or 5 years. Planned future occurrence: Units or subjects from which the information Households. is extracted Territorial signification National level and 3 climatic zones (NUTS1). Effectiveness The coverage rate of the criteria of the Task Force 2008 is 31.15%. Efficiency The cost per household examined was 115. Accuracy, reliability and quality Spreading Accessibility Total score 31,2% Must have criteria 33% Nice to have 35% Renewables criteria 0% Energy poverty 0% Data registered by meters are complemented with data from questionnaires and electricity consumption bills. A quality control on preliminary results is performed. Data are validated with other IDAE's studies. Results and methodology are included in the report "Analyses of the energy consumption of the household sector in Spain", published in July The report on methodology and results is on the Internet in the web site 50

51 Strengths and weaknesses TABLE 26. SPAIN: STRENGTHS AND WEAKNESSES OF IN SITU MEASUREMENT SPAHOUSEC-SECH MEASURES ELECTRICITY CONSUMPTION IN 600 HOMES STRENGTHS AND WEAKNESSES OF THE IN SITU MEASUREMENT: SPAHOUSEC-SECH MEASURES ELECTRICITY CONSUMPTION IN 600 HOMES (SPAIN) Strengths Weaknesses Registration of data by meters is objective. This approach differentiates by climate zone, seasons of the year, type of dwelling, working days and holidays, type of electric appliance and end use of the electric energy. Data from meters are complemented with data from questionnaires and electricity bills. Both a bottom-up and a top-down approach are implemented. General standby electricity consumption is estimated A quality control on preliminary results is carried out Data are validated with other IDAE's studies. This entire method is a complement to a more global project that aims at measuring energy consumption in households, so its specific focus on electric energy cannot be considered as a disadvantage. The Project itself has been pioneer in some aspects, such as the measurement of the standby. Only data related to electricity consumption and expenditure is collected. The source from which electricity comes is not considered, which prevents for analyzing questions about renewables. Penetration of energy efficiency technologies is not measured Metering of domestic electricity use at apparatus level in 400 households (Sweden) The main purpose of this source is to obtain a more accurate breakdown of electricity use at appliance level. It covers energy efficiency of electrical appliances and lamps as well, and some other variables concerning household characteristics and housing stock characteristics. This source is also used for validating national energy statistics. A remarkable feature of this source consists in the fact that it measures the stand by power consumption. The coverage rate of the criteria of TF2008 is not very low, despite the fact that this source focuses only on electricity consumption. In this sense the coverage of the category RENEWABLES is 20%, as this source measures aspects concerning renewable energies that 51

52 take the form of electricity. The coverage rate of the criteria within the categories MUST HAVE and NICE TO HAVE is roughly one third, as the whole coverage rate. Data are validated with additional and external information, and plausibility automated checks are performed. On the other hand only in one tenth of the sample the measurements were implemented during the whole year, 40 households out of 400; in the rest, the measurements were performed only during one month. These figures suggest that perhaps the extrapolation to annual consumption of the population could not be as accurate as it would be desirable. 52

53 Characteristic Elements TABLE 27. SWEDEN: CHARACTERISTICS ELEMENTS OF IN SITU MEASUREMENT METERING OF DOMESTIC ELECTRICITY USE AT APPARATUS LEVEL IN 400 HOUSEHOLDS 53

54 Characteristic elements TABLE 28. SWEDEN: STRENGTHS AND WEAKNESSES OF IN SITU MEASUREMENT METERING OF DOMESTIC ELECTRICITY USE AT APPARATUS LEVEL IN 400 HOUSEHOLDS Similarities and differences found between the in situ measurements Both sources measure electricity consumption at appliance level, differentiate by end uses, including stand by power, and use questionnaires that complete the information collected. Regarding housing stock characteristics, the Spanish in situ measurement takes into consideration the type of dwelling as well as the Swedish one. On the other hand the latter takes into account the age of the building, whilst the Spanish does not. Both sources include socioeconomic variables, the Spanish by means of the selection of the places (city/town/rural area) where the dwellings of the sample are placed, and the Swedish by means of the questionnaires filled previously to the implementation of the in situ measurement, in a direct manner. However, the Spanish source also directly collects information about energy consumption habits. The Spanish source collects information on expenditure, as it collects electricity bills; on the contrary, the Swedish in situ only measures energy consumption. In this sense, even considering only energy consumption, the Spanish method is richer, because it includes information from electricity invoices. The Swedish in situ measurement collects information on penetration of energy efficiency technologies regarding lamps and electrical appliances, and partially covers the 54

55 category of penetration of renewables associated with electricity. In relation to these two fields the Swedish source is superior to the Spanish one, which does not collect information on the previously referred variables. An important difference between the two sources consists of the periods during which the measurements are performed. The Spanish method covers ten months of the year in all the dwellings of the sample, and extrapolates the results to the whole year by assimilating spring with autumn. The Swedish method only implements the measurements during the whole year in one tenth of the sample; in the rest of the cases, electricity consumption is measured only during one month. The sizes of the samples of the two in situ measurements are not very different, 600 dwellings in the Spanish case and 400 dwellings in the Swedish in situ, especially if we consider the differences in population between the two countries. So, it can be presumed that the Spanish source is more accurate than the Swedish one regarding the measurement and estimation of annual electricity consumption at appliance level, even if we take into account that Spanish climate conditions vary more during the year than climate conditions in Sweden. Finally, the coverage rate of the criteria of the Task Force of 2008 is higher in the Spanish source, due to its higher coverage of the variables into the category MUST HAVE MODELS Five have been the very best Models selected from all the countries analyzed: the first four in the category of comprehensive models, and the fifth in the category of models aimed at checking different statistical sources. Model of energy consumption in households. Slovenia. RAKLAMM calculation model for space and water heating. Finland. Analysis of sectoral energy consumption by end-use. Switzerland. BREHOMES models national aggregates of domestic energy use. United Kingdom. Matching the results of "Household electricity consumption survey" with "Household energy consumption survey". Austria. In the following sections the characteristic elements of each model, its strengths and weaknesses and the similarities and differences found between them as well as an analysis of the ability of each one to be transferred to other countries will be analyzed Model of energy consumption in households (Slovenia) The model developed by Slovenia has been selected as the first best practice according to methods in this category of information source, because it is very useful for determining energy consumption in households by end use. 55

56 By means of modeling the information achieved from even five different sources, the model results widely reach the main purposes established: to acquire data on energy consumption in households by end use and type of energy commodity; to acquire data on the consumption of electricity by end use or type of appliance and to acquire data on the types of space and water heating systems (local/central/district heating) and energy commodities used for them. As result of this the method gets data on energy consumption for five of the six the end-uses which the Task Force establishes and for nine fuel types covering all the main energy sources. This model is perfectly applicable in the rest of countries of the EU, according to the quantity and quality of the achieved data. The model of Slovenia and the model of Finland, that will be analyzed forward, are appreciated as the two models that should be replicated in the rest of the European countries. This evaluation is based on their high effectiveness and efficiency. The model of Slovenia uses data from the survey on energy consumption in households, which is an ad hoc survey with that purpose. Due to the fact that in the EU there are 15 countries that have a clearly defined ad hoc surveys of such a type, this model may be perfectly transferred. At the same time, in those countries where there is no such a survey, the model may be replicable in order to get the main data on energy consumption in households specified by the TF2008. Besides, the model performs a validation of the data. Model assumptions are in a first phase based on the analysis of responses from the Household Energy Consumption Survey, and in a second phase adjusted so that the total energy consumption is equal to the statistical data for the entire country the calibration of the model. 56

57 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA ANALYSIS OF THE USES AND RESULTS OF THE MODEL COMPENDIUM OF BEST PRACTICES Characteristic elements TABLE 29. SLOVENIA: CHARACTERISTICS ELEMENTS OF THE MODEL OF ENERGY CONSUMPTION IN HOUSEHOLDS CHARACTERISTIC ELEMENTS OF THE MODEL OF ENERGY CONSUMPTION IN HOUSEHOLDS (SLOVENIA) Characteristic element Description MODEL PURPOSE To acquire data on energy consumption in households by end use and type of energy commodity. To acquire data on the consumption of electricity by end use or type of appliance. To acquire data on the types of space and water heating systems (local/central/district heating) and energy commodities used for them. KEY METHODOLOGICAL ELEMENTS Comprehensiveness Results' reconciliation with other data Quality of the inputs used. The model uses several sources (more than 5) of different types. Data from the ad-hoc Household Energy Consumption Survey carried out in the country, data from energy supply collected by different statistics surveys, and data from administrative sources such as: Census of population, SORS, Real Estate Register, Eco Fund Slovenian Environmental Public Fund, etc. Methodology. For the estimation of the space heating consumption the model discriminates between areas of single and multi-family buildings divided into classes of energy efficiency and into sparsely and densely populated areas. In addition, it includes assessment of residents behaviour in relation to energy efficiency, a factor of climate variability and many technologies for producing the required energy. For the estimation of water heating consumption the model differences between cold and heated water (50 C) and the population of Slovenia. For the estimation of energy consumption of appliances each appliance represents its sub-model based on the number of appliances in households, their distribution by age and energy efficiency class and household behaviour of appliance use. The model obtains data on energy consumption for five of the six the end-uses which the Task Force establishes and for nine fuel types covering all the main energy sources: wood, coal, petroleum, gas, electricity and renewables. In addtition, the model collects data on electricity consumption broken down by several types of appliance. So that, this model shows a high comprehensiveness degree in measuring the energy consumption in the residential sector. Model assumptions are in the first phase based on analysis of responses from Household Energy Consumption Survey, and in the second phase adjusted so that the total energy consumption is equal to the statistical data for the entire country. Effectiveness of the model Publicity and availability of results and methodology The model results widely reach the main purposes established: to acquire data on energy consumption in households by end use and type of energy commodity; to acquire data on the consumption of electricity by end use or type of appliance and to acquire data on the types of space and water heating systems (local/central/district heating) and energy commodities used for them. The results of the modelling are a part of the data on consumption of energy in households which are published by the Statistical Office of the Republic of Slovenia. Regular recurrence (frequency) The frequency of the results generated by the model is according to the frequency of its main sources: the Household Energy Consumption Survey is performed every three years, while the other energy statistics data are available annually. The coverage rate of this source in the requirements included in the Task Force 2008 has Total coverage rate been: 60.8%. Must have criteria The weighted score achieved is: 62% Nice to have The weighted score achieved is: 50% Renewables criteria The weighted score achieved is: 100% Energy poverty The weighted score achieved is: 0% 57

58 Strengths and weaknesses TABLE 30. SLOVENIA: STRENGTHS AND WEAKNESSES OF THE MODEL OF ENERGY CONSUMPTION IN HOUSEHOLDS RAKLAMM calculation model for space and water heating (Finland) The model implemented by Finland has been selected as best practice according to statistical methods in this category. This election is strongly based on the objectives and results of the model. The model obtains data on energy consumption by two end-uses (space and water heating) and by eight fuel types essential in the space and water heating consumption: wood, peat, coal, fuel oil, natural gas, electricity, district heating and heat pumps. So that this model measures rather good the energy consumption in the residential sector for two end uses included in the Task Force: the space heating and the water heating. In the calculations of energy consumption by uses main and supplementary heating have been considered, and intensity of occupation of dwelling too. In the elaboration of this model even 10 different sources have been used, which means a great amount of information. Nevertheless, the data that are based on a bottom-up approach are compared with the total consumption of the corresponding source of energy. estimation. If there is any difference, then the data are corrected by means of expert It is also remarkable that the model is maintained and updated annually, by means of estimations in the intermediate years, though that supposes an economic effort (around 10,000 per year). The goodness of the model is recognized and space heating data are published on an annual energy statistics compilation. The data are also published annually as part of the statistics on energy consumption in households. Besides, there is an extensive and comprehensive methodological report of the model. This model is perfectly replicable in other countries, as the model of Slovenia (previously commented), due to its low cost, the existing knowledge of its methodology and its high coverage of the main items of the TF2008. In the case of those countries where an ad hoc survey or a comprehensive 58

59 survey is not available, as in Finland, with this model the main requirements of Eurostat are perfectly covered Characteristic elements TABLE 31. FINLAND: CHARACTERISTICS ELEMENTS OF THE RAKLAMM CALCULATION MODEL FOR SPACE AND WATER HEATING 59

60 60

61 Strengths and weaknesses TABLE 32. FINLAND: STRENGTHS AND WEAKNESSES OF OF THE RAKLAMM CALCULATION MODEL FOR SPACE AND WATER HEATING BREHOMES models national aggregates of domestic energy use (United Kingdom) The model BREHOMES developed by The Building Research Establishment under contract with the Department of Energy and Climate Change, allows the estimate of the main variables of energy consumption in the residential sector. This is fundamental for this kind of statistics, especially when there isn t any kind of ad hoc survey on energy consumption in households, as it is the case of the United Kingdom. For that reason, this model is of vital importance. This model, by means of different sources, proves to be effective in order to acquire data on energy consumption in households by end use and type of energy commodity, to estimate heat losses (total, by zone, by element) and to estimate floor areas. Moreover, this model provides inputs for other models that manage to provide information on energy consumption in households in the United Kingdom. 61

62 It is based on detailed bottom-up approach so it can be used to look at effects of energy efficiency policies at the level of individual technologies. It is also remarkable that this type of model has been developed for more than 3 decades, which allows detecting trends of energy consumption in households regarding the data managed. This fact also involves that a constant update and improvement of the model is needed for preventing its obsolescence in relation to other statistical methods that measure energy consumption in households On the other hand this so comprehensive type of models may involve high costs for the country that wants to implement it. With respect to this, the cost of this model is 400,000. For this reason, before its implementation, it would be needed to consider whether this is the method economically more efficient. 62

63 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA ANALYSIS OF THE USES AND RESULTS OF THE MODEL COMPENDIUM OF BEST PRACTICES Characteristic elements TABLE 33. UNITED KINGDOM: CHARACTERISTICS ELEMENTS OF THE BREHOMES-MODELS NATIONAL AGRREGATES OF DOMESTIC ENERGY USE CHARACTERISTIC ELEMENTS OF THE BREHOMES MODELS NATIONAL AGGREGATES OF DOMESTIC ENERGY USE (UNITED KINGDOM) Characteristic element MODEL PURPOSE KEY METHODOLOGICAL ELEMENTS Description To estimate the energy consumption by end use (space heating, water heating, cooking, lighting and appliances) and by fuel type (electricity, gas, oil, solid fuel). To estimate heat losses. To estimate floor areas. Quality of the inputs used. The model uses four sources of different types: two surveys (the English Housing Survey and the Family Expenditure Survey, both annual), a model (the Market Transformation Programme) and other source (the Housing and Construction Statistics). Other inputs used by the model are: U-values for each element for different standards of insulation; floor areas for each category; heating patterns for different categories; water heating type by space heating type; heating system efficiencies (from MTP boiler model); lights and appliances use (from DECADE); cooking use (from DECADE); number of occupants information; external temperatures / degree days; internal demand temperatures (these are used as parameters to reconcile the model with DUKES, but the values used must be plausible and be consistent with available information). Methodology. The model takes a bottom-up approach from the different sources used to obtain elements such as the insulation, the heating system, the lights and appliances of a house for over 1000 dwelling categories defined by type, age, tenure, and ownership. The characteristics of the housing stock are then fed into another country model named BREDEM which performs multiple runs to cover different heating patterns in different types of dwelling, and the results scaled and aggregated according to the number of buildings in each category. Furthermore, these characteristics of the housing stock are reconciliated with the Housing Stock Energy Consumption and other UK Energy Statistics to output the demand temperature which is introduced again to BREHOMES. Comprehensiveness The model obtains data on energy consumption for five of the six the end-uses which the Task Force establishes and for the main the five main fuel types: wood, coal, petroleum, gas and electricity. So that, this model shows a high comprehensiveness degree in measuring the energy consumption in the residential sector. Results' reconciliation with other data Effectiveness of the model Data are compared with energy balance figures at an aggregate level, and usually agree to within a few percent. Trend data are also used to check the consistency of the data received each year. The model results widely reach the main purposes established: to acquire data on energy consumption in households by end use and type of energy commodity; to estimate heat losses (total, by zone, by element) and to estimate floor areas. Publicity and availability of results and methodology Regular recurrence (frequency) Total coverage rate The model results are annually published in the Domestic Energy Factfile ct/dom_fact.aspx They are also used in the compilation of the Energy Consumption in the UK tables which are published by the Department of Energy and Climate Change The frequency of the results generated by the model is annual. The coverage rate of this source in the requirements included in the Task Force 2008 has been: 20.6%. Must have criteria The weighted score achieved is: 24% Nice to have The weighted score achieved is: 0% Renewables criteria The weighted score achieved is: 0% Energy poverty The weighted score achieved is: 0% 63

64 Strengths and weaknesses TABLE 34. UNITED KINGDOM: STRENGTHS AND WEAKNESSES OF THE BREHOMES-MODELS NATIONAL AGRREGATES OF DOMESTIC ENERGY USE Analysis of sectorial energy consumption by end-use (Switzerland) The target of this model, regarding the residential sector, is the estimation of total energy consumption by the end-uses space heating, water heating, cooking, and other electrical appliances and lighting, in order to make useful analysis of energy perspectives. The approach of this model is bottom-up. It uses as inputs the results of many different statistical sources, and it is a very comprehensive model as it has as outputs energy consumption by end use, by energy commodity, and by type of appliance. In addition, its results are reconciled with the outputs of many other statistical experiences. This model includes a wide variety of variables regarding the end uses considered, as well as some variables regarding energy efficiency of buildings. On the other hand, variables related to households income are not taken into account, which prevents analyzing such subjects as energy poverty or economic relationships in the field of energy consumption in the residential sector. The end use space cooling is not considered properly, which is not desirable as regards cross-national comparability. 64

65 It is noticeable that this model is operational for the elaboration of the Swiss energy policy. The whole coverage rate of the TF2008 criteria is high compared with those of the rest of the models; these criteria within the category RENEWABLES are fully covered. The most remarkable features of this model are its comprehensiveness, the great number of inputs included, and the great number of statistical sources which the outputs are reconciled with. 65

66 Characteristic elements TABLE 35. SWITZERLAND: CHARACTERISTIC ELEMENTS OF THE MODEL ANALYSIS OF SECTORIAL ENERGY CONSUMPTION BY END-USE 66

67 Strengths and weaknesses TABLE 36. SWITZERLAND: STRENGTHS AND WEAKNESSES OF THE MODEL ANALYSIS OF SECTORIAL ENERGY CONSUMPTION BY END-USE Matching the results of "Household electricity consumption survey" with "Household energy consumption survey" (Austria) This is a very specific model regarding both its purpose and its number of variables, but it allows a detailed breakdown of non thermal use of electricity on the basis of the Household Energy Consumption survey. It uses as inputs the outputs of two surveys, the survey Household Energy Consumption and the survey Electricity and Gas Journal. This model manages to match 11 variables that are present in both surveys, and the donor data records are those of the survey Electricity and Gas Journal, because the information they provide on power consumption related to non thermal uses is more detailed. The model is concerned directly with non thermal end uses, which are lighting and electrical appliances, and stand by power (space cooling is not considered separately). But with the help of this model, and using the two surveys which it is related with, energy consumption data by the end uses space heating, water heating, cooking, lighting and electrical appliances, and stand-by are achieved. The model includes as variables key socioeconomic information, which allows for a rich analysis of energy consumption in households. However, some important issues regarding this field are not covered, such as penetration of energy efficiency technologies, renewables and energy poverty, neither is properly covered intensity of energy service 67

68 demand. Nevertheless, in spite of its specificity, the coverage rate of the criteria of the Task Force of 2008 is very low: 8.2%. It is remarkable the success of this model in achieving its target, i.e. the data matching. In addition, it was possible to confirm and quantify the expected relationships and effects of the parameters used on household power consumption. Besides, the outputs are reconciled with other relevant statistical sources. Finally, detailed reports on results and methodology, and resulting analysis by means of the model, are provided in detail on the Internet. 68

69 FULFILLEMENT OF THE TASK FORCE 2008 CRITERIA ANALYSIS OF THE USES AND RESULTS OF THE MODEL COMPENDIUM OF BEST PRACTICES Characteristic elements TABLE 37. AUSTRIA: CHARACTERISTIC ELEMENTS OF THE MODEL MATCHING THE RESULTS OF HOUSEHOLD ELECTRICITY CONSUMPTION SURVEY WITH HOUSEHOLD ENERGY CONSUMPTION SURVEY CHARACTERISTIC ELEMENTS OF THE MODEL Matching the results of "Household electricity consumption survey" with "Household energy consumption survey" (AUSTRIA) Characteristic element PURPOSE OF THE MODEL KEY METHODOLOGICAL ELEMENTS Description To estimate end-use energy consumption. To estimate regional household energy consumption. To estimate household power consumption in urban and rural areas. To complement data collected in a survey. 11 variables which were present in all data records, were used for the matching, whereby the data records from the Electricity and Gas Journal served as the "donor data records" for the "recipient data records" of the Household Energy Consumption survey because of the detailed information they contained regarding power consumption for non-thermal uses In addition to information about the heating system, overall power consumption, power consumption for space heating, water heating and cooking, the model also included socio-economic criteria relating to household members, property-related criteria (age of property, living area, number of dwellings in the property) and regional criteria (urban versus rural regions) The next step in further developing and fine-tuning the generated model was the development of another survey with detailed information on non-thermal uses (refrigeration and freezing, large household appliances, lighting, entertainment and office electronics, standby consumption etc.) in 2012 and to integrate the information from this survey into the existing model Comprehensiveness Energy consumption data by the end uses space heating, water heating, cooking, lighting and electrical appliances, and stand-by are achieved with the help of this model (space cooling is not considered separately, but in the category lighting and electrical appliances) However the model aims specifically at non thermal end uses, which are lighting and electrical appliances (space cooling is included in this category), and stand by; for this reason the operational energy commodity regarding this model is electricity Results' reconciliation with other data Effectiveness of the model Publicity and availability of results and methodology This model obviously reconciles data from Household Energy Consumption with data from Electricity and Gas Journal, as this is its purpose The results are reconciled with other relevant information sources such as the Household Energy Use survey The aims of the project were achieved in their entirety in terms of content, i.e. the detailed information from the donor data set (Electricity and Gas Journal) was successfully transferred to the recipient data set (Household Energy Consumption) It was possible to confirm and quantify the expected relationships and effects of the parameters used on household power consumption A detailed report on results and methodology is available on the Internet at on_of_households/index.html Regular recurrence (frequency) The modelling is performed every two years, when the results of the survey "Energy consumption in private households" are available, and updated every four years, when current donor data records from the survey "Electricity and natural gas consumption by purposes" are available Total coverage rate 8.2% Must have criteria 10% Nice to have 0% Renewables criteria 0% Energy poverty 0% 69

70 Strengths and weaknesses TABLE 38. AUSTRIA: STRENGTHS AND WEAKNESSES OF THE MODEL MATCHING THE RESULTS OF HOUSEHOLD ELECTRICITY CONSUMPTION SURVEY WITH HOUSEHOLD ENERGY CONSUMPTION SURVEY Similarities and differences found among the models Similarities: The four first models have been selected because they fulfill a twofold purpose: estimation of energy consumption both by end-uses and by type of fuel. The main similarities among them come from the quality and amount of data sources used as input (all of them show a high level in such aspect) and from the uses and results. In detail, all the models carry out reconciliation process in their results, show a high effectiveness in achieving the purpose established, have a high regular recurrence and rather good publicity of both the results and the methodology (special mention has to be done for the excellent methodological report in the case of the Finnish model). The fifth model has not a comprehensive nature, its purpose is very specific, the linkage between data of two important surveys on energy consumption in households. But it is similar to the previous four models regarding effectiveness, reconciliation of results, coverage rate of the criteria of TF2008, and publicity of results and methods. 70

71 Differences: The four first referred models are highly comprehensive, but they are so at different degrees. The main differences among them come from the comprehensiveness level for measuring the energy consumption in the residential sector and from some specific methodological issues. The Slovenian, Swiss and British models estimate the energy consumption by five of the six end uses established for the Task Force, so they are extremely comprehensive in measuring the energy consumption in the residential sector. On the contrary, the Finnish model only measures two end uses so its comprehensiveness degree in such measurement is lower. In addition, while the Slovenian, the British and to a lesser extent the Swish models add some specific purposes to the main one of achieving the energy consumption by end uses and fuel types (i.e. he consumption of electricity by end use or type of appliance, the type of space and water heating systems,) the Finnish one only covers the main purpose. The Austrian model has a different nature, as it has been previously commented, and it is specifically focused on the end-uses electrical appliances and lighting. As for the methodological issues, the Finnish model seems to be the most refined in its procedures for the correction of non valid data and for estimating the data in the intermediate years of the modeling process. The Austrian model excels at the precision of its results, due to same extent to its high specificity INTEGRATED APPROACHES Spain Integrated Approach It must be pointed out that concerning the method named integrated approach only two countries have provided information, Spain and Norway. It may be that other countries have this kind of information source, but with other name or classified into some other statistical method. It has been noticed that many countries validate and check the data achieved by means of the different sources used, but further knowledge has been not available. Nevertheless, in the cases of those countries that perform similar procedures via modeling, these procedures have been taken into account in the evaluation of best practices according to the statistical method modeling. Taking into consideration that there is information on this method only for two countries, Spain has been chosen as the best documented method and with the best results. The integrated approach of Spain is a statistical method that has served to check and validate data coming from the different statistical sources used for the achievement of information on energy consumption in the residential sector. In the case of Spain various modules of integrated approach are performed, such as: Dwelling and Household Features; Household equipment; 71

72 Aggregate energy consumptions by energy sources; Energy Consumptions by Services/Uses and by Energy Sources In the first module, the differences that may be noticed are quite irrelevant. In the second module, adjustment methods used has been twofold: 1. Supplementary adjustment: used when some given equipment has been reported by some of the operations carried out but not by others. In this case, the equipment rate resulting from the operation which reported on the said equipment has been assumed. 2. Inter-operational adjustment: this kind of adjustment has been used when several operations have informed about the same equipment with different rates in a range of 25% over the equipment. There are two casuistries for this issue: The equipment rates of the three operations fall within the 25% range: it is adjusted to the equipment rate through the weighted average of all three operations. The equipment rates of two operations fall within the 25% range, and the third operation is over: in this case, the adjustment is made through weighted averages with the equipment rates of the two operations found between the 25% range. The third module has been implemented in several phases: Phase 1. The collected information, in every climate zone, and in survey and interview, has been applied a filter consisting in initially discarding the energy costs and consumptions exceeding the average price by 5%. Phase 2. The interviewees with a face-to-face survey that have initially been discarded by the former filter have been contacted anew so as to amend their data. Phase 3. All the interviews outside the allowed variation ranges of average prices have been recalculated in terms of costs and energy consumptions, depending on the very features of the relevant household. There is always a residue of approximately 7% of rejected interviews in terms of cost and energy costs. Phase 4. Once the energy consumptions and costs for the various surveys have been adjusted, as it happened with the equipment, a new adjustment and balancing between the different surveys has been done, using a similar method: 1. Additional setting: used when a specific cost or energy consumption has been informed by some of the operations performed and not the other. In this case, it has been assumed rate resulting from the operation which reported on such consumption. 2. Inter-operational setting: this type of adjustment was used when multiple operations have reported the same cost or energy consumption with different values in the range of 15% on the rate of cost or energy consumption. In the last module the method used has been: The information supplied by natural gas marketers is broken down by climate zones, the month of consumption and two types of fees: the one relating to households consuming 72

73 natural gas for cooking and sanitary hot water, and the one in households with consumptions in cooking, sanitary hot water and heating. Consumptions devoted to cooking have been inferred taking into account the consumptions measured for electric cookers, affected by a performance of 85% of the gas and LPG cookers. These consumptions are subtracted from the aggregate consumptions by energy source, leaving a residue ascribable solely to the associated consumptions of sanitary hot water and heating Characteristic elements TABLE 39. SPAIN: DWELLING AND HOUSEHOLD FEATURES 73

74 TABLE 40. SPAIN: HOUSEHOLD EQUIPMENT 74

75 TABLE 41. SPAIN: AGGREGATE ENERGY CONSUMPTIONS BY ENERGY SOURCES 75

76 TABLE 42. SPAIN: ENERGY CONSUMPTIONS BY SERVICES/USES AND BAY ENERGY SOURCES 76

77 3. BEST PRACTICES BY GEOGRAPHICAL AREAS The UE countries selected to be included in the Compendium of Best Practices by Geographical Areas are: Austria, Cyprus, Greece, Latvia, Slovenia and Spain. These countries reached good results in the previous analysis of best practices and therefore each one will be studied in order to determine the reasons of their success. Among the non UE countries, USA has been selected to be deeply analyzed in this report due to the good results it achieved in the analysis of geographical best practices CYPRUS The first country to be analyzed is Cyprus which achieves good results with a very simple statistics. TABLE 43. CYPRUS: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE Note: The valuation achieved by the countries by means of the SCI is biased in favor of those which have participated in a SECH project. It seems required to emphasize that Cyprus has only two data sources: Energy consumption in households and Model related to Survey on Energy Consumption in Households. They both have reached very good positions in the different rankings of best practices according to statistical methods. Furthermore, their sources have achieved notable scores both in Task Force 2008 coverage rate and in best practices assessments 77

78 according to operational criteria. That is the reason why Cypriot statistics have been considered to belong to the top group. It must be pointed out that Cyprus has developed a SECH project, so that the implemented methodology has been focused on processing energy consumption statistics in residential sector. Specifically, this methodology has been expressly designed to cover all the requirements established by the working group in The final result of Cyprus regarding Synthetic Coverage indicator was 79.2%. This score is a consequence of their high coverage of Must have categories. They manage to calculate final energy consumption by end-use (e.g. space heating, water heating, space cooling, cooking, lighting and electrical appliances) by means of their model. Nevertheless, every other requirement fulfilled by Cypriot sources has been achieved through their survey Energy Consumption in Households. In this way, both categories related to space heating, water heating, cooking and air conditioning and housing stock/household characteristics are almost completely collected due to the completeness of the said survey. Nice to have and Renewables categories, the ones considered to be less relevant after the implementation of the weighting process, are partly covered by the means of this survey too. Thus, they have carried out a very complete process in order to collect data regarding energy consumption, with respect to the type of dwellings and the demographic characteristics of households, the type of end use categories and the various energy sources. The sampling methodology has been quite thorough. The accuracy of the answers has been sought: all completed questionnaires have been checked and corrected for any differences or logical inconsistencies. In the case of unusual answers or missing data, the respondents have been contacted again. The sampling frame (based in 2001 census) was updated in 2009 regarding number of households and population, and it was representative for rural and urban areas. Validation and default tests have been conducted too. Besides, information from energy suppliers has been utterly useful to crosscheck some pieces of data. However, some issues related to the frequency of the survey have not been clearly expressed. The following table shows the advantages and disadvantages revealed by Cyprus (as a country) regarding the methodology used to collect energy consumption statistics in residential sector: TABLE 44. CYPRUS: STRENGTHS AND WEAKNESSES 78

79 3.2. GREECE Secondly, Greece has also shown an outstanding methodology, which has reached good results in the best practices ranking regarding geographical criteria. Energy consumption statistics in Greek residential sector are based on two data sources (one survey and one model), an administrative source and a survey (both utilized to contrast some data). TABLE 45. GREECE: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE Note: The valuation achieved by the countries by means of the SCI is biased in favor of those which have participated in a SECH project. Therefore, Greece has also received very good marks, mostly because of the great quality of their ad-hoc survey (a SECH project called Survey on Energy Consumption in households). The rest of sources (ELSTAT and Households' budget survey) play a residual 79

80 role. The model Bottom-up approach provides broken down data regarding consumption of commodities and energy service demand. The said ad-hoc survey covers a lot of categories regarding Task Force 2008 requirements: energy consumption by end-use (space heating and cooking), consume/expenditure of energy commodities, housing stock/household characteristics and categories regarding to space heating, water heating, cooking and air conditioning. 81% of the Must have requirements are covered by means of these data. In addition, some variables related to electrical appliances, energy service demand ( Nice to have ) and Renewables are also collected through the survey Energy Consumption in Households. The others sources play a complementary role and cover variables like Biomass (ELSTAT). The Bottom-up approach model aims to compile data regarding energy consumption in several sectors. In this way, it cannot be considered to be a model expressly designed for residential sector. Consequently, it provides a lower input in this analysis. TABLE 46. GREECE: STRENGTHS AND WEAKNESSES One important detail must be highlighted: Greek methodology is in development, so that certain results remain unknown. Furthermore, the structure of the methods is similar to the Cypriot one, despite the fact that the model developed by Greece provides less information and involves an important additional cost. This last aspect has a crucial relevance nowadays: financial problems can question the continuity of the data collection LATVIA Latvia is the next country whose statistics are going to be analyzed. Latvia has reached an outstanding result regarding the Synthetic Coverage Indicator due to the complementarity acquired through their two sources (Household Energy Consumption Survey and Breakdown of energy consumption in households by type of consumption). It 80

81 can be affirmed that Latvian statistics have been capable of collecting several important items and reaching a high response rate in view of the necessity of collect data related to energy consumption in households. TABLE 47. LATVIA: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE Note: The valuation achieved by the countries by means of the SCI is biased in favor of those which have participated in a SECH project. With respect to Task Force 2008 criteria coverage, they also reached a high score (80,9%). On the one hand, requirements like consumption/expenditure of energy commodities, data concerning space heating, water heating, cooking or air conditioning, housing stock characteristics and penetration of renewable energy sources are collected through the ad-hoc survey. In this way, Latvia covers 86% of Must have criteria, 50% of Nice to have criteria and 100% of Renewables criteria. Nevertheless, coverage regarding unit/specific consumption data variables has been achieved thanks to their model. Thus, the two sources play a complementary role and manage to cover a 68% of the criteria. 81

82 TABLE 48. LATVIA: STRENGTHS AND WEAKNESSES It seems required to comment that Latvia is able to compile energy consumption in households through only two different sources (similar to the Cypriot and the Greek case) SLOVENIA The case of Slovenia is also very peculiar: they only have two sources (Household Energy Consumption Survey and Model of energy consumption in households) but they achieve to complement each other in order to cover an important list of items. TABLE 49. SLOVENIA: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE Note: The valuation achieved by the countries by means of the SCI is biased in favor of those which have participated in a SECH project. In this case, the result obtained regarding Task Force 2008 coverage was 81,6%. The modeling of energy consumption by end-use was achieved through the source Model of energy consumption in households (it was also useful in order to determine unit/specific 82

83 consumption data too). The rest of Must have categories like consumption/expenditure of energy commodities, penetration of energy efficiency technologies and housing stock characteristics and the data collected regarding Nice to have and Renewables have been compiled using both sources. On the one hand, they show high quality competence when it comes to developing preliminary projects: they are extremely helpful in order to find out those steps, phases, activities, etc. that can cause trouble when collection data process has to be made. On the other hand, their model includes relevant adjustments and characteristics: this way they are capable of executing reliable estimations. Nevertheless, some mistakes should be corrected regarding sampling methodology: for example, they ought to specify the type of elements that form the whole sample. Another important detail is the fact that they also collect information concerning energy consumption of vehicles, although this issue is not part of this study. TABLE 50. SLOVENIA: STRENGTHS AND WEAKNESSES 83

84 For all the above, it is extremely important to point out that the calculation of data regarding energy consumption in households of Slovenia is based on and complements appropriately their ad-hoc survey SPAIN Relating to the Spanish case, they have reached a good position in the best practices. TABLE 51. SPAIN: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE Note: The valuation achieved by the countries by means of the SCI is biased in favor of those which have participated in a SECH project. 84

85 The main purpose of the different sources is to determine the basic parameters of the residential sector, as well as the global and segmented energy consumption by uses and services associated with the sector. This information is segmented and systematized according to different areas: kinds of accommodations, climate zones, types of services, types of applications or uses. In order to develop the field word, it has been necessary to analyse and define the sample sizes and the problems associated with the phone survey and face to face survey to be used before undergoing the field works, with a view to guaranteeing a sufficient degree of confidence, with a maximum deviation under ±3% in the crossings resulting from the combination of the three climate zones and the two types of dwellings considered The methodology of Spain consists in the combination of the various methods and information sources which may enable to determine the consumption of the residential sector through a bottom-up approach. The information resulting from the integration of the various methods used is eventually checked against the existing official energy information available in the residential sector, usually obtained through top-down procedures, and which is also checked up with consumption calculations on the basis of equipment and average consumption. Their statistics manage to cover a lot of categories thanks to the abundance of different sources (surveys, in-situ measurements, administrative sources and integrated approaches). However, Spanish sources that have been more highlighted due to their great quality are the in-situ measurement, the integrated approaches, one administrative source (Electricity, natural gas and GPL surveys) and two surveys (SPAHOUSEC-SECH project telephone survey and SPAHOUSEC-SECH project panel survey). The various methods used all along the implementation of this projec, each of the procedures and specific and the differentiated objectives are supplementary, which enables to reach greater understanding of the energy consumption in the sector. These methods stem from the choice of a statistically representative sample, both at national level and at the level of climate zones, as well as of the type of dwelling, of the permanently occupied houses, considered relevant for energy purposes in this project. Respecting Spain s coverage rate, it is achieved by means of several sources (surveys, insitu measurements, administrative sources and integrated approaches). The final consumption by end-use, which is one of the main objectives of their studies, has been covered by means of the method of integrate approach (Energy consumptions by service/use and by energy sources module). Data from marketers, traders and measurements has been used in order to reach conclusions on that subject. Other categories, like consumption/expenditure of energy commodities, space heating, water heating, cooking and household/housing stock characteristics, electrical appliances, are collected through a few sources at the same time. Variables regarding Renewables and penetration of energy efficiency technologies categories have been covered using panel, telephone surveys and other sources too. 85

86 TABLE 52. SPAIN: STRENGTHS AND WEAKNESSES For all the above, Spanish sources have considered to be outstanding regarding best practices criteria. The fact that they owe an important amount of sources makes possible the compilation of a lot of items and their breakdown AUSTRIA Austria is one of the selected countries for a deeper analysis. The table below reveals the sources that constitute their statistics on energy consumption in the residential sector: 86

87 TABLE 53. AUSTRIA: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE Note: The valuation achieved by the countries by means of the SCI is biased in favor of those which have participated in a SECH project. One critical factor that should be pointed out is the fact that they show an important amount of sources: some of them are aimed to fulfill requirements like the determination of the energy consumption by end-use (for example, their ad-hoc survey Energy consumption in households ) whereas others purpose is to provide several complementary but relevant data (for instance, Temperature adjustment with heating degree days model). Accordingly, they reach a notable result regarding Task Force 2008 coverage rate: 78,7%. Additionally, it must be emphasized that they achieve an outstanding score concerning Must have categories (83%). 87

88 Concerning the methodology used in order to cover the categories established by the Task Force 2008, they manage to collect the most important data by means of their surveys. Nevertheless, their models play a very important role when estimating specific variables: for example, the energy consumption by end-use. Furthermore, they use remarkable techniques to carry out both collection and modeling processes. They take into account a lot of characteristics when the time comes for sampling and dealing with information. Moreover, comparisons can be made due to the fact that calculations are executed yearly. TABLE 54. AUSTRIA: STRENGTHS AND WEAKNESSES Consequently, it can be affirmed that Austrian statistics excel at developing figures on energy consumption in households. That is the reason why this country has been included in the top group. As a conclusion, it seems necessary to emphasize the fact that all these countries analyzed above are part of the SECH project. This detail involves some crucial factors: several commonalities can be identified (they all have achieved a remarkable score regarding Task Force 2008 coverage rate, they have highly covered most of Must have categories, etc.). Additionally, these said projects enable any interested person/institution the study of statistics concerning energy consumption in residential sector of any of these countries due to their notable transferability. 88

89 3.7. USA USA is the best Non-European country relating to statistics on energy consumption in the residential sector. The most important feature regarding statistics on energy consumption in households in USA is the existence of an integrated and well-established statistical framework, which allows allocating resources, minimizing costs, optimizing results and clarifying the research. This framework is made up of basically of the RECS, the Household Survey, the Rental Agent Survey, the Energy Supplier Survey, and the model "Modeling the data from the Household and Energy Supplier Survey"; the main pieces of this framework are the RECS and the referred model. This results in high quality data and results. The range of relevant variables measured is very wide, which makes possible very rich analyses. The global coverage of the criteria of the Task Force of 2008, measured by the Synthetic Coverage Indicator (SCI), is one the most higher among all the countries that have been analyzed. Specifically, the coverage within the categories NICE TO HAVE, RENEWABLES, and ENERGY POVERTY is 100%. The procedure implemented by USA as regards statics on energy consumption in households might encounter some difficulties regarding transferability, as a key piece of it, the Residential Energy Consumption Survey (RECS), which has a voluntary character, implements a face-to-face procedure that is very exhaustive and involves physical inspections of the dwelling and energy invoices. On the other hand, this statistical framework is possible thanks to the expertise of the American staff and the economic resources available. TABLE 55. USA: STATISTICAL METHODS, PURPOSES AND COVERAGE RATE Note: The valuation achieved by the countries by means of the SCI is biased in favour of those which have participated in a SECH project. 89

90 TABLE 56. USA: STRENGTHS AND WEAKNESSES 90